MarinOne Scripts Creator's Corner
Share and Learn Problems Solved by MarinOne Scripts
Category Action Type - Bulk Upload (Preview)
Purpose:
The Python script automates the pausing and resuming of webinar ads based on their month-to-date (MTD) spending relative to a predefined monthly budget.
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The Python script automates the pausing and reactivation of webinar creatives based on their cost, ensuring efficient budget management.
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The Python script categorizes pacing percentages into descriptive tags such as “On Target” or “Over Pacing” based on predefined ranges.
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The Python script extracts and updates GUIDs from campaign names in a dataset, ensuring only valid entries are retained.
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The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget targets and current spending.
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The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
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The Python script processes campaign data to update the status and paused date based on specific conditions.
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The script processes and tags dimensions in a dataset related to campaigns, publishers, and accounts.
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The Python script categorizes marketing campaigns into different strategies based on their Return on Advertising Spend (ROAS) performance.
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The Python script assigns a specific strategy to campaigns based on the account name when the strategy is initially unassigned.
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The script pauses keywords with 0 conversions and 60+ clicks in the last 60 days, ensuring they have been active for at least 60 days.
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The Python script processes account data to filter and transform it for structured budget allocation purposes.
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The script processes and merges campaign budget data from a primary data source and Google Sheets to update daily budgets for campaigns.
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The Python script maps Salesforce (SFDC) input data to a structured format for further analysis and reporting.
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The Python script processes campaign data to extract and map program codes to their full names, filtering out entries where this mapping fails.
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The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscore.
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The script extracts and tags the SFDC ID from campaign names in a dataset by identifying the value after the last ‘|’ character.
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The Python script calculates and adjusts bid modifications for different devices (mobile, tablet, desktop) based on CPA and ROAS strategy constraints for advertising campaigns.
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The Python script assigns a strategy name to each campaign by extracting it from a specific field in the campaign data.
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The Python script processes marketing data to determine and populate the ‘NTB Uplift’ metric based on specific conditions related to revenue and new customer acquisition.
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The Python script automatically maps advertising campaigns to specific strategies based on conversion rates and Return on Advertising Spend (ROAS) metrics over defined periods.
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The script automates the process of setting daily budgets for campaigns by merging data from a primary data source with a Google Sheets reference.
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The script automates the process of pausing and reactivating advertising campaigns based on their daily budget utilization.
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The Python script pauses keywords with more than 100 clicks and a cost per conversion above €2 for the last 7 days.
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The Python script pauses keywords in a report that have between 10 and 100 clicks and a cost per conversion greater than €2.80 over the last 7 days.
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The Python script pauses keywords with more than 10 clicks and a conversion rate below 10%.
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The Python script dynamically allocates temporary traffic budgets based on recommended daily budgets from input data.
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The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
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The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
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The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 33-day lookback period, excluding the most recent day.
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The Python script tags campaigns based on their performance metrics compared to predefined benchmarks.
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The Python script identifies and recommends pausing keywords that are at least 30 days old, have zero conversions, and a quality score below 5.
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The script qualifies suggested keywords based on conversion rates, CPA thresholds, and token count limits for effective ad targeting.
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The Python script processes and merges campaign budget data from a primary data source and a Google Sheets reference to prepare a structured budget allocation for campaigns.
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The Python script automatically tags PS Clients based on specific keywords found in campaign names.
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The script updates monthly budget targets for strategies by matching them with concatenated values from a Google Sheet.
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The Python script adjusts bid ratios for mobile, tablet, and desktop devices in advertising campaigns based on gross profit-weighted average bids.
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The Python script calculates the adjusted daily budget for various strategies based on remaining budget and days in the month.
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The Python script synchronizes campaign budget data from a primary data source with updates from a Google Sheets reference, ensuring daily budget allocations are current.
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The script ensures that any campaign with a daily budget below $50 is adjusted to meet this minimum threshold.
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The script assigns the ‘Auto Pause Status’ of ‘traffic’ to new campaigns that are part of a strategy but have not yet been assigned this status.
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The Python script processes and displays the initial rows of a primary data source for structured budget allocation workflows.
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The script automatically pauses campaigns in a dataset if their associated event dates have passed.
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The Python script parses campaign names to extract and tag seminar details such as format, location, registration target, and seminar code.
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The Python script automates the process of enabling a campaign override flag when adjusted recommendations exceed predefined caps set in Google Sheets.
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The script parses campaign names to automatically tag hotel-related campaigns with specific Marin Dimensions tags, handling special cases for certain account names.
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Automates the population of utmcampaign and utmmedium dimensions based on campaign name and campaign type values.
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The Python script ingests media plan spend targets from a Google Sheets document and maps them to strategies for the current month.
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
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The script identifies conflicting keywords between current and negative keyword lists in an account.
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Lookup new month’s spend target and update via strategy bulk file
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Python script that takes the unspent Strategy Spend Target from the previous month and adds it to the current Spend Target.
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Python script to pause campaigns when the monthly spend reaches the monthly budget stored in the strategy.
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Tag AdGroup if CPA performance is abnormally high within Campaign 30-lookback excluding recent 3 days
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The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script automates the process of updating strategy spend targets by copying monthly budget data from customer-maintained Google Sheets and matching it with strategies in Marin.
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The Python script processes campaign data to extract and categorize specific dimensions such as geo, segment, targeting, and platform from campaign names.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
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The Python script identifies and tags geographical regions in campaign names based on predefined keywords.
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The Python script processes campaign data to extract and tag platform and targeting information from campaign names.
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Calculate the percentage difference between the current daily budget and the SBA recommended daily budget for campaigns.
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Automating Dimension Tagging with the landing page in the dimension “Landing Page Dim” and the keyword and match type combination in the dimension “Keyword MatchType Dim”.
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Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
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Python script to add a tag to a campaign name based on a specified separator.
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Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
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The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script generates negative keywords for single keyword campaigns by cross-negating keywords within each account.
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The Python script automates the process of copying and updating monthly budget allocations from Google Sheets to a structured budget allocation system by matching campaign strategies.
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Python script that pauses and re-enables campaigns based on their monthly spend and budget.
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The Python script calculates pacing metrics and recommended daily budgets for digital advertising campaigns based on various campaign parameters and goals.
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
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The script pauses advertisements if they have zero conversions after spending $100.
Purpose
Pauses ads that have a CPA of $150+ over the previous 7 days
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their goals within specified timeframes.
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The Python script automates the process of setting dimensions based on campaign names for marketing campaigns.
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The script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets for Google Smart Bidding strategies.
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The Python script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets, specifically supporting Google Smart Bidding strategies.
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The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose Python script that solves the problem of allocating budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget....
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The Python script identifies ad groups within campaigns that have abnormally high Cost Per Acquisition (CPA) performance, tagging them as outliers.
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The Python script optimizes budget allocation for advertising campaigns to minimize lost impression share due to budget constraints.
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The script parses campaign names to automatically tag them with a region-specific dimension based on predefined rules.
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This Python script solves the problem of calculating various metrics and values for pacing and budget allocation in a digital advertising campaign.
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
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The Python script monitors campaign spending and recommends pausing campaigns if projected costs exceed the monthly budget.
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SBA Campaigns Watcher
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The Python script calculates and manages pacing and budget allocation for advertising campaigns based on various metrics and goals.
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The Python script processes campaign data to aggregate metrics like cost, clicks, and impressions over specified date ranges for each campaign, ensuring unique campaign entries.
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Python script to update campaign information based on specified conditions.
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The script extracts and updates specific campaign details from campaign names in a dataset.
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The Python script calculates the remaining days for each campaign based on its start date and updates a CSV file with this information.
Purpose
Parse out and populate Pacing - Start Date and Pacing - End Date in ISO format from the Campaign column of a DataFrame.
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign
Purpose
Python script to pause and re-enable campaigns based on budget allocation.
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Python script to auto-push a subset of suggested keywords from a keyword recommendations grid.
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The script automates the process of setting all active Google Product Groups to Bid Override with no end date.
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The Python script updates the status, target CPA, and daily budget for new launch campaigns based on specified ROAS criteria.
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The Python script automates the update of campaign statuses, bid strategies, and target CPA for new launch campaigns based on performance metrics.
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The Python script updates the status, target cost-per-acquisition (tCPA), bid strategy, and maturity of new launch campaigns based on specified return on ad spend (ROAS) criteria.
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The script enforces monthly budget caps for advertising strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
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Python script for negative keyword expansion.
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Python script solves the problem of adjusting the Publisher Target ROAS for Google campaigns based on the daily spend goal and publisher cost.
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The Python script adjusts search bid values and bid override statuses for keywords in advertising campaigns based on specific performance criteria.
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The Python script assigns campaign dimension values based on specific patterns found in campaign names.
Purpose
Reduce the daily budget of campaigns by 20% if the GAAP profit from the previous day is less than 0.
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The Python script assigns a specific campaign strategy and publisher strategy based on the current date matching the “CPA Date” in the data.
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The Python script evaluates advertising campaigns to determine if they meet specific criteria for switching to a new publisher bidding strategy based on minimum ROAS and spend thresholds.
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The script categorizes Yahoo DSP ad groups into ‘New’, ‘Mature I’, and ‘Mature II’ based on their spending over the previous 7 days.
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The script adjusts the daily budget of campaigns by increasing it by 20% if the daily spend exceeds 60% of the current daily budget.
Purpose
Pushes new Strategy Targets at start of month
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The Python script processes marketing data to assign strategies based on performance metrics over specific time periods.
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Tag AdGroup if CPA performance is abnormally high within Campaign
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The Python script processes keyword data to manage and optimize advertising campaigns by pausing certain keywords based on performance metrics.
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Python script to add dimensions tag based on campaign name.
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Python script to add a dimensions tag based on the campaign name.
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The script adjusts the target CPA and daily budget of Google campaigns based on recent ROAS and spending data.
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The script identifies and pauses mature advertising campaigns with low Return on Ad Spend (ROAS) over the past 14 days.
Purpose
The script adjusts the target cost-per-action (tCPA) for campaigns based on their current cost per conversion, increasing it if the cost is below a specified threshold.
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The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘Mature’ based on their ROAS over the previous 14 days.
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The Python script categorizes ExplorAds and Yahoo DSP campaigns into maturity labels based on their spending thresholds over the past year.
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The Python script automates the process of pausing keywords and labeling them with the ‘AutoPause’ dimension based on specific criteria related to creation date, accumulated clicks, and spend.
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The Python script automates the process of switching campaign publisher bidding strategies to Target CPA based on minimum spend and ROAS criteria.
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The Python script automates the process of pausing new advertising campaigns with low Return on Advertising Spend (ROAS) based on predefined criteria.
Purpose
The script increases the daily budget for campaigns with an impression share greater than a specified percentage over the last specified number of days.
Purpose: The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘New Launch’ through ‘New - Round 5’ based on their ROAS over the past...
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The Python script categorizes campaigns into ‘Brand’ or ‘Non-Brand’ based on their names and outputs the results.
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The Python script assigns a specific label to campaigns based on certain conditions in a dataset.
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The script parses campaign names to extract and assign a tag based on a specific naming convention.
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The Python script enforces monthly budget caps for strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose: The script automates the creation of suggested keywords from a keyword expansion report, focusing on long keywords with six or more tokens and setting them with specific attributes for...
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The Python script identifies and tags campaigns with significantly lower Return on Advertising Spend (ROAS) compared to their peers within the same account.
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The Python script reassigns advertising strategies to campaigns based on their Month-to-Date conversion levels.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose: The Python script adjusts campaign budgets by increasing them by 5% if the Cost Per Acquisition (CPA) performance is 10% better than the average of peers within the same...
Purpose: The Python script adjusts the budget of non-brand advertising campaigns by 5% if their cost-per-acquisition (CPA) performance is 10% better than the average of their peers within the same...
Purpose
Pause campaigns with no active groups.
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The Python script identifies and tags AdGroups with a Cost Per Acquisition (CPA) significantly higher than their peers within the same campaign over a 30-day period.
Category Item Changed - AdGroup
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
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The script pauses ad groups with fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The Python script pauses ad groups with over 100 clicks that have not generated any Prime Starts/Conversions in the past 30 days, ensuring they have been active for at...
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The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
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The Python script processes account data to filter and transform it for structured budget allocation purposes.
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The script extracts the country code from a group name by identifying the segment before the first hyphen.
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The Python script calculates and adjusts bid modifications for different devices (mobile, tablet, desktop) based on CPA and ROAS strategy constraints for advertising campaigns.
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The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 33-day lookback period, excluding the most recent day.
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The Python script adjusts bid ratios for mobile, tablet, and desktop devices in advertising campaigns based on gross profit-weighted average bids.
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The script automates the process of tagging groups with fund type dimensions by matching data from a primary source with a reference Google Sheet.
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The Python script tags groups with a FUND dimension based on abbreviations found in group names.
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The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria within a dataset.
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The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
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Automates the process of updating UTM group dimensions based on ad group names by replacing spaces with plus signs.
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The script automatically pauses campaigns in a dataset if their associated event dates have passed.
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The Python script extracts a title from a “Group” column using a regex pattern and updates the “Title” column accordingly.
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The Python script tags Meta Ad Groups based on their performance metrics, categorizing them as “winning” or “losing” according to predefined business rules.
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The script extracts and assigns a country code from a group name into a designated column based on specific parsing rules.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
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The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a dataset, ensuring it is reset to an empty state.
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The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a data set, effectively resetting its values.
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The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
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The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose
The script extracts the country code from a group name by identifying the segment before the first hyphen and assigns it to a ‘Country Code’ dimension.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign 30-lookback excluding recent 3 days
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose
Python script to pause ad groups in select model-based new vehicle campaigns if there are 3 or fewer vehicles in stock.
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The Python script identifies ad groups within campaigns that have abnormally high Cost Per Acquisition (CPA) performance, tagging them as outliers.
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The script assigns Meta ABO Budget values at the group level for active Meta Ad sets, removing any previously assigned values at the campaign level.
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The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
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The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
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The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
Purpose
Python script to tag ad groups if their CPA performance is abnormally high within a campaign.
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Tag AdGroup if CPA performance is abnormally high within Campaign
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The Python script identifies and tags AdGroups with abnormally low Cost/Conversion performance within a campaign over a specified lookback period.
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The Python script categorizes media types and sub-types based on specific keywords found in account, campaign, and group data.
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The Python script categorizes media types and sub-types based on specific account and group criteria in a dataset.
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The Python script categorizes media types and sub-types based on specific keywords found in account and campaign data.
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The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
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The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
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The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
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The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
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The script updates custom parameters for keywords with specific tags in the landing page result column.
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The script updates custom parameters for keywords with specific tags in the landing page result column.
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The script categorizes Yahoo DSP ad groups into ‘New’, ‘Mature I’, and ‘Mature II’ based on their spending over the previous 7 days.
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign
In a Nutshell
The script processes PPC campaign data to update event names based on specific patterns in group names.
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The script checks if the “IB Last Updated” date is two or more days old and flags it for alert if certain conditions are met.
Purpose
Auto Pause After Event Date
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The script determines auction boost amounts for groups in specific campaigns based on various criteria, including pageviews, PUP scores, and shoot prices.
Purpose: The Python script dynamically adjusts bid values for ad groups based on historical and target Return on Advertising Spend (ROAS) to optimize advertising strategies across clients in the Dutch...
Purpose
Clear Daily Winner and Overspend labels daily
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Tag AdGroup Dimensions per ROAS/CPA Performance
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The Python script identifies and tags AdGroups with abnormally low ROAS performance within a campaign over a specified lookback period.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose:
The Python script identifies and tags AdGroups with a Cost Per Acquisition (CPA) significantly higher than their peers within the same campaign over a 30-day period.
Category Linked Datasource - M1 Report
Purpose:
The Python script automates the pausing and resuming of webinar ads based on their month-to-date (MTD) spending relative to a predefined monthly budget.
Purpose:
The Python script automates the pausing and reactivation of webinar creatives based on their cost, ensuring efficient budget management.
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The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
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The Python script categorizes pacing percentages into descriptive tags such as “On Target” or “Over Pacing” based on predefined ranges.
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The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
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The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
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The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
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The Python script extracts and updates GUIDs from campaign names in a dataset, ensuring only valid entries are retained.
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The Python script dynamically allocates recommended daily budgets to campaigns based on input data.
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The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
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The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget targets and current spending.
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The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
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The Python script processes campaign data to update the status and paused date based on specific conditions.
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The Python script adjusts revenue and conversion data at the keyword level based on latency factors to provide more accurate estimates.
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The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds and generating a report for analysis.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
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The script adjusts revenue and conversion data based on latency factors to provide more accurate estimates.
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The Python script identifies outliers in campaign metrics and calculates anomalies using adjustable thresholds to generate a weekly report.
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The script processes and tags dimensions in a dataset related to campaigns, publishers, and accounts.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
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The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
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The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
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The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
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The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The Python script categorizes marketing campaigns into different strategies based on their Return on Advertising Spend (ROAS) performance.
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The Python script assigns a specific strategy to campaigns based on the account name when the strategy is initially unassigned.
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The Python script processes and merges financial data to calculate adjusted publication costs for the latest available date.
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The Python script processes account data to filter and transform it for structured budget allocation purposes.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
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The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
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The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
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The Python script automates the process of updating daily budget allocations for advertising campaigns based on recommended values.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
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The script compares daily budget allocations to actual spending to assess pacing and budget status for advertising campaigns.
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The Python script automates the merging and filtering of data from multiple sources to facilitate structured budget allocation for CCT incentives.
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The Python script identifies and reports anomalies in monthly campaign metrics using configurable thresholds for outlier detection.
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The script processes and merges campaign budget data from a primary data source and Google Sheets to update daily budgets for campaigns.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
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The Python script maps Salesforce (SFDC) input data to a structured format for further analysis and reporting.
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The script extracts the country code from a group name by identifying the segment before the first hyphen.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
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The script extracts country codes and friendly names from campaign names in a dataset.
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The Python script processes campaign data to extract and map program codes to their full names, filtering out entries where this mapping fails.
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The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscore.
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The Python script extracts the ‘REF Marker’ from the ‘Landing Page’ column and assigns it to the ‘REF Marker’ dimension in a structured data format.
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The script extracts and processes Marketo IDs from campaign names in a dataset.
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The Python script processes campaign data to extract and map program codes to their full names, creating a structured output for further analysis.
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The script automatically labels campaign dimensions based on the campaign naming convention and campaign type.
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The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscores.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
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The script extracts and tags the SFDC ID from campaign names in a dataset by identifying the value after the last ‘|’ character.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
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The Python script calculates and adjusts bid modifications for different devices (mobile, tablet, desktop) based on CPA and ROAS strategy constraints for advertising campaigns.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
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The Python script assigns a strategy name to each campaign by extracting it from a specific field in the campaign data.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
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The Python script processes marketing data to determine and populate the ‘NTB Uplift’ metric based on specific conditions related to revenue and new customer acquisition.
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The Python script categorizes pacing percentages into descriptive tags such as ‘On Target’, ‘Under Pacing’, ‘Over Pacing’, etc., based on predefined ranges.
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The Python script automatically maps advertising campaigns to specific strategies based on conversion rates and Return on Advertising Spend (ROAS) metrics over defined periods.
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The script transfers Microsoft purchase conversion data into a new column labeled “Last365Days Conversions” within a dataset.
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The script automates the process of setting daily budgets for campaigns by merging data from a primary data source with a Google Sheets reference.
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The script automates the process of pausing and reactivating advertising campaigns based on their daily budget utilization.
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The Python script pauses keywords with more than 100 clicks and a cost per conversion above €2 for the last 7 days.
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The Python script pauses keywords in a report that have between 10 and 100 clicks and a cost per conversion greater than €2.80 over the last 7 days.
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The Python script pauses keywords with more than 10 clicks and a conversion rate below 10%.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script automates the pausing and re-enabling of advertising campaigns based on their monthly budget targets and current spending.
Purpose: The Python script manages campaign budgets by automatically pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget and re-enabling them when the spend falls below the budget....
Purpose
The Python script automates the process of allocating and updating daily budgets for advertising campaigns based on recommended values from a data source.
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The Python script dynamically allocates and updates daily budgets for advertising campaigns based on recommended values.
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The Python script extracts and tags the campaign strategy from the campaign name based on specific delimiters.
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The script extracts and tags the numeric value before the first dash in a campaign name, removing any parentheses.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script dynamically allocates temporary traffic budgets based on recommended daily budgets from input data.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
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The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
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The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The Python script attributes quality call conversions to keywords based on their click weight.
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The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 33-day lookback period, excluding the most recent day.
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The Python script tags campaigns based on their performance metrics compared to predefined benchmarks.
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The Python script identifies duplicate keywords in advertising campaigns and recommends which ones to pause based on performance metrics.
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The Python script identifies and recommends pausing keywords that are at least 30 days old, have zero conversions, and a quality score below 5.
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The script qualifies suggested keywords based on conversion rates, CPA thresholds, and token count limits for effective ad targeting.
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The Python script assigns a strategy to campaigns that are currently marked as ‘Unassigned’ based on a specific naming pattern.
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The Python script processes and merges campaign budget data from a primary data source and a Google Sheets reference to prepare a structured budget allocation for campaigns.
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The Python script adjusts daily budgets for advertising campaigns based on pacing cycles and specific criteria to optimize spending.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
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The Python script automatically tags PS Clients based on specific keywords found in campaign names.
Purpose
The script updates monthly budgets for strategies by matching them with concatenated values from a Google Sheet.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
The script updates monthly budget targets for strategies by matching them with concatenated values from a Google Sheet.
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The Python script identifies weekly anomalies in campaign performance metrics using configurable thresholds and generates a summary report.
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The Python script automatically tags manufacturer names based on keywords found in campaign names within a dataset.
Purpose: The Python script calculates the pacing of advertising strategies at the campaign level by comparing month-to-date spending against expected spending based on the total budget and elapsed days in...
Purpose:
The Python script calculates the adjusted daily budget for strategies at the campaign level based on remaining budget and days left in the month.
Purpose: The Python script identifies weekly anomalies in campaign performance metrics by analyzing outliers using configurable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a specified...
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The Python script calculates predictive revenue values for campaigns using gross lead data and program-level revenue and conversion rates.
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The Python script sets benchmarks for individual campaigns and strategies by analyzing performance metrics over specified time periods.
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The Python script tags county codes to campaigns based on their names in a DataFrame.
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The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
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The Python script adjusts bid ratios for mobile, tablet, and desktop devices in advertising campaigns based on gross profit-weighted average bids.
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The Python script transfers values from the “Portfolio” column to the “Amazon Portfolio” column in a dataset.
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The Python script calculates the adjusted daily budget for various strategies based on remaining budget and days in the month.
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The script automates the process of tagging groups with fund type dimensions by matching data from a primary source with a reference Google Sheet.
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The Python script tags groups with a FUND dimension based on abbreviations found in group names.
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The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
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The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
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The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
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Automatically tags the “Product” dimension based on the product detail page URL of an ad.
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The Python script identifies outliers in weekly campaign performance metrics using adjustable thresholds and generates a report accommodating conversion lag.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose: The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a configurable lookback...
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose
The script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies outliers in weekly campaign metrics using adjustable thresholds for anomaly detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
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The Python script synchronizes campaign budget data from a primary data source with updates from a Google Sheets reference, ensuring daily budget allocations are current.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script generates a weekly report to identify anomalies in campaign metrics using configurable thresholds for outlier detection and deviation analysis.
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The Python script automatically tags marketing campaigns with a service dimension based on the campaign name.
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The Python script tags product types based on campaign names in a DataFrame.
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The script identifies and tags US states mentioned in the “Campaign” column of a DataFrame.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
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The Python script detects and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
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The script ensures that any campaign with a daily budget below $50 is adjusted to meet this minimum threshold.
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The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria within a dataset.
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The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
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The Python script sets a Target CPA Cap of $1000 for all active strategies or campaigns where the current CPA exceeds this limit.
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The Python script identifies and analyzes anomalies in weekly campaign metrics to highlight outliers and trends for marketing performance evaluation.
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The Python script clears existing dimension values to ensure only the top 20 keywords are labeled for the next day’s dimension script.
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The Python script identifies and labels the top 10 performing keywords based on cost per conversion from a sorted report.
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The script identifies and tags the top-performing keywords in a Google Ads report based on cost per conversion.
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The Python script identifies and analyzes anomalies in weekly campaign performance metrics over the past eight weeks for Powpow Enterprise Retail.
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The script assigns dimension labels to campaigns based on their naming conventions and campaign types.
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Automates the process of updating a remarketing dimension in a dataset based on specific campaign name values.
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Automates the process of populating the brand dimension in a dataset based on specific rules applied to campaign name and type values.
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Automates the categorization of campaigns by analyzing campaign names and assigning them to predefined categories.
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Automates the process of populating device and match type dimensions in a dataset based on campaign name values.
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Automates the process of populating subregion dimensions in a dataset based on campaign name values.
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The script assigns the ‘Auto Pause Status’ of ‘traffic’ to new campaigns that are part of a strategy but have not yet been assigned this status.
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The Python script categorizes PPC scores into letter grades ranging from A to D based on predefined score ranges.
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Automates the process of updating UTM group dimensions based on ad group names by replacing spaces with plus signs.
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Automates the population of utmcampaign and utmmedium dimensions based on campaign name and type.
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The Python script processes and displays the initial rows of a primary data source for structured budget allocation workflows.
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The script automatically pauses campaigns in a dataset if their associated event dates have passed.
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The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
The Python script processes keyword data to generate a structured keyword template based on specific group terms.
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The Python script parses campaign names to extract and tag seminar details such as format, location, registration target, and seminar code.
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The Python script automates the process of enabling a campaign override flag when adjusted recommendations exceed predefined caps set in Google Sheets.
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The script parses campaign names to automatically tag hotel-related campaigns with specific Marin Dimensions tags, handling special cases for certain account names.
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The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using adjustable thresholds.
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The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget specified in the strategy.
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The Python script identifies and reports conversion anomalies at the campaign level by analyzing weekly data and applying statistical methods to detect outliers.
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This Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
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The Python script identifies and tags the top 10 keywords as “Top Performer” based on cost per conversion over the last 60 days for each school program.
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The Python script identifies and reports conversion anomalies at the campaign level for a dental network by analyzing weekly performance data.
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The Python script processes a DataFrame to extract and categorize information about campaigns, including studio names, feed categories, and language targets.
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The Python script updates benchmark dimensions in Marin by copying data from a staging Google Sheet, matching the ‘Abbreviation’ column with the ‘Strategy’ column.
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The Python script processes a DataFrame to extract and replace search phrases from keywords based on a given title, creating a new column with the modified keyword.
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The Python script extracts a title from a “Group” column using a regex pattern and updates the “Title” column accordingly.
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Automates the population of utmcampaign and utmmedium dimensions based on campaign name and campaign type values.
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The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds and historical data analysis.
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The Python script calculates and tags campaigns with strategy-level benchmark scores for metrics such as MTD Gross Lead, CPL, CPL Trend, and Interview Rate.
Purpose
The script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose
The Python script ingests media plan spend targets from a Google Sheets document and maps them to strategies for the current month.
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The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
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The script identifies ads with expired or nearly expired application deadlines across all publishers.
Purpose: The Python script tags Meta Ads campaigns at the ad level based on performance metrics such as eCPM and CTR, categorizing them as “winning” or “losing” according to predefined...
Purpose:
The Python script tags Meta Ad Groups based on their performance metrics, categorizing them as “winning” or “losing” according to predefined business rules.
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
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The script extracts and assigns a country code from a group name into a designated column based on specific parsing rules.
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The script extracts and categorizes campaign types and game names from campaign names in a dataset.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
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The Python script tags Meta campaign dimensions based on performance metrics to determine if they are “winning” or “losing.”
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The script identifies and reports anomalies in weekly campaign conversions by analyzing deviations from forecasted metrics.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
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The script identifies conflicting keywords between current and negative keyword lists in an account.
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The Python script identifies and recommends pausing keywords in advertising campaigns that are at least 30 days old, have zero conversions, and a quality score below 5.
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The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose
The Python script identifies and reports on campaign performance anomalies by detecting outliers in key metrics using configurable thresholds and generates a weekly report accommodating conversion lag.
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Matches the SBA Strategy Name and Targets to the Dynamic Allocation ones.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose: The Python script compares the CPA (Cost Per Acquisition) for campaigns between the current quarter and the last week, flagging those with a CPA for the last week that...
Purpose:
The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a dataset, ensuring it is reset to an empty state.
Purpose:
The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a data set, effectively resetting its values.
Purpose:
The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose:
The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose:
The script identifies and tags the top 10 keywords as “Top Performer” based on conversion count and cost per conversion over the last 60 days.
Purpose:
The Python script tags campaigns based on their performance metrics compared to predefined benchmarks, assigning tags like “Over Target,” “Under Target,” and “On Target.”
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The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
The script extracts the country code from a group name by identifying the segment before the first hyphen and assigns it to a ‘Country Code’ dimension.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
The script automates the extraction and tagging of the “Country Code” dimension from campaign names for Carburant’s Square Enix, excluding Meta publishers.
Purpose
Lookup new month’s spend target and update via strategy bulk file
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion metrics and cost efficiency over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion and cost per conversion metrics over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 performing keywords based on conversion and cost per conversion over the last 60 days.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose
Python script that takes the unspent Strategy Spend Target from the previous month and adds it to the current Spend Target.
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The Python script extracts and assigns a campaign type from campaign names based on a specific tag format.
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The Python script extracts project numbers from campaign names by identifying tags that appear after a specified delimiter and assigns them to a designated dimension.
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The script updates the ‘Campaign CPA This Quarter’ column with the current quarter’s CPA values for each campaign.
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The Python script updates strategy spend targets by copying program budgets from Google Sheets to a local data structure.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose
Python script to copy values from the ‘Strategy’ and ‘Strategy Target’ columns to the ‘SBA Strategy’ and ‘SBA Campaign Budget’ columns, respectively.
Purpose
Python script to pause campaigns when the monthly spend reaches the monthly budget stored in the strategy.
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign 30-lookback excluding recent 3 days
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script generates a performance anomaly report for pay-per-click marketing campaigns.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script automates the process of tagging campaigns with the appropriate program manager based on data from Google Sheets.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script automates the process of updating strategy spend targets by copying monthly budget data from customer-maintained Google Sheets and matching it with strategies in Marin.
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The Python script processes campaign data to extract and categorize specific dimensions such as geo, segment, targeting, and platform from campaign names.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
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The Python script processes campaign data to identify and tag audience and segment information based on predefined keywords.
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The Python script identifies and tags geographical regions in campaign names based on predefined keywords.
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The Python script processes campaign data to extract and tag platform and targeting information from campaign names.
Purpose:
The Python script extracts and categorizes geographical, segment, targeting, and platform information from campaign names in a dataset.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
Purpose:
The script extracts keyword match types from campaign names and updates a data frame accordingly.
Purpose:
The Python script identifies and tags the intent of marketing campaigns based on specific keywords found in campaign names.
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The Python script processes campaign data to extract and assign topics based on a structured naming convention.
Purpose
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend approaches or exceeds the monthly budget set in a strategy.
Purpose:
The Python script manages the automatic pausing and re-enabling of advertising campaigns based on monthly budget targets defined in strategies.
Purpose
Python script to pause and resume campaigns based on monthly budget spend.
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The Python script extracts and tags the “F-YY-Brand” from campaign names in a dataset, ensuring structured budget allocation.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose:
The script extracts and categorizes tags from non-brand campaign names in a dataset.
Purpose:
The Python script automates the process of calculating and adjusting daily budgets for marketing campaigns based on structured budget allocation (SBA) strategies.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
Purpose:
The script identifies campaigns with a significant discrepancy between the assigned “Two Year Cost (Publisher)” and the actual publisher cost over the last two years.
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The Python script alerts the Program Manager when the percentage difference in a dataset is 15% or more, either positively or negatively.
Purpose
Campaigns Anomaly
Purpose:
Calculate the percentage difference between the current daily budget and the SBA recommended daily budget for campaigns.
Purpose
Python script to pause ad groups in select model-based new vehicle campaigns if there are 3 or fewer vehicles in stock.
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Automatically tags marketing campaigns as either Brand or NonBrand based on their names.
Purpose
Automating Dimension Tagging with the landing page in the dimension “Landing Page Dim” and the keyword and match type combination in the dimension “Keyword MatchType Dim”.
Purpose
Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for Category.
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Python script to parse campaign names and add campaign-level Marin Dimensions Tag for campaign type.
Purpose
Campaign Performance Anomaly Report with Summary
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The script automates the assignment of bidding strategies to campaigns based on their creation date.
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The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
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The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
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The script automates the assignment of bidding strategies to campaigns based on their creation date.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
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The Python script automatically assigns a campaign to a specific bidding strategy based on the campaign’s age.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
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Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
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The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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Python script to add a tag to a campaign name based on a specified separator.
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This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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The script updates the “Keyword Cost/Conv Performance” dimension for keywords whose cost per conversion is 30% greater than their campaign’s cost per conversion.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and remaining weekdays in the month.
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Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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The Python script updates the “Campaign 30 Day Cost per Conversion” dimension daily to support keyword-level anomaly detection for cost per conversion.
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Pause Poor performing Keywords with 0 Conv. and QS <5
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The Python script identifies and tags campaigns where the previous day’s spending is at least 90% of the daily budget and certain conditions are met.
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies and tags campaigns where the publisher cost for the prior day is at least 90% of the daily budget, indicating a potential budget cap situation....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the publisher cost for the prior day is at least 90% of the daily budget and flags them as “Budget Capped.”
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the previous day’s spending was at least 90% of the daily budget and flags them if certain conditions are met.
Purpose: The Python script identifies campaigns where the previous day’s spending is at least 90% of the daily budget and flags them as “Budget Capped” if certain conditions are met....
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The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
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Parse Campaign Name and add Campaign-level Marin Dimensions Tag for Placement.
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Campaign Performance Anomaly Report with Summary
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The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds for interquartile range and deviation.
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Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
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The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script identifies keywords with duplicate MKWID values and prepares them for reupload with blank custom parameters.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and potential spend.
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Auto Tag Campaign with Tipo de Campanha Dimension
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The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
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Automatically tags campaigns with ‘Brand’ or ‘NonBrand’ based on specific keywords in the campaign name.
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Auto Tag the funnel stage of campaigns based on the campaign name.
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The Python script generates negative keywords for single keyword campaigns by cross-negating keywords within each account.
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Calculates the difference between SBA allocation and the percentage of total publication cost.
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The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
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The Python script identifies and reports campaign-level outliers in key conversion metrics, such as Total AMU Sign-Ups and Podcast First Stream, by calculating anomalies using adjustable thresholds.
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The Python script automates the process of copying and updating monthly budget allocations from Google Sheets to a structured budget allocation system by matching campaign strategies.
Purpose: The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by calculating recommended daily budgets based on historical spend, remaining budget, and pacing...
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The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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Python script that pauses and re-enables campaigns based on their monthly spend and budget.
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SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
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The Python script extracts specific information from campaign names and organizes it into a structured format for further analysis.
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
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The Python script calculates pacing metrics and recommended daily budgets for digital advertising campaigns based on various campaign parameters and goals.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and calculating deviations using adjustable thresholds.
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This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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Remove the dollar sign ($) from the SBA Campaign Budget column in a given input dataframe.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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Python script to filter and process campaign data based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
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Python script to filter and process campaign data based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
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Python script to filter and manipulate data from a primary data source based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
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The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
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Python script to filter and process campaign data based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script solves the problem of calculating various metrics and values for a campaign, such as total pub cost, total impressions, total clicks, total views, pacing cycle start...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
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The script pauses advertisements if they have zero conversions after spending $100.
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Pauses ads that have a CPA of $150+ over the previous 7 days
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The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their goals within specified timeframes.
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The Python script automates the process of setting dimensions based on campaign names for marketing campaigns.
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The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
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The script calculates and stores the average cost-per-click (CPC) for the last 28 days in a specified dimension called “Test.”
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The Python script identifies performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts based on historical trends.
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Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
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The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose Python script that solves the problem of allocating budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget....
Purpose The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and rolling up performance metrics to dimensions such as Product Category and Brand/Generic, using adjustable IQR and...
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The Python script identifies ad groups within campaigns that have abnormally high Cost Per Acquisition (CPA) performance, tagging them as outliers.
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The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script detects performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts derived from historical trends.
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Campaign Anomaly Detection
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Python script solves the problem of generating a performance anomaly report for pay-per-click marketing data.
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The Python script automatically pauses or resumes marketing campaigns based on their month-to-date (MTD) spending relative to a predefined budget cap.
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The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation (SBA) processes.
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The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The script automatically tags campaigns as “Brand” or “Non-Brand” based on the campaign name, specifically tagging as “Non-Brand” if the name starts with ‘EEE’.
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The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The Python script automates the process of tagging campaigns with combined school and program dimensions and assigns an SBA strategy based on these tags.
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Python script that combines the ‘School’ and ‘Program’ columns into a new column called ‘School_Program’ and assigns the created tag to the ‘School_Program’ column.
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The script parses campaign names to automatically tag them with a program identifier based on a specific naming convention.
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The Python script parses campaign names to automatically tag them with a school dimension based on the text before the first underscore.
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The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation.
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The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The Python script optimizes budget allocation for advertising campaigns to minimize lost impression share due to budget constraints.
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The script parses campaign names to automatically tag them with a region-specific dimension based on predefined rules.
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The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose
This Python script solves the problem of calculating various metrics and values for pacing and budget allocation in a digital advertising campaign.
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The Python script is designed to optimize daily budget allocation for Search SBA strategies by minimizing lost impression share due to budget constraints.
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The script assigns Meta ABO Budget values at the group level for active Meta Ad sets, removing any previously assigned values at the campaign level.
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The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
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The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
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The Python script identifies and filters paused CCT groups based on a specific date range.
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The Python script identifies and filters paused CCT groups based on a specific date range.
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The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
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The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
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The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
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The Python script monitors campaign spending and recommends pausing campaigns if projected costs exceed the monthly budget.
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SBA Campaigns Watcher
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The Python script identifies and filters paused CCT groups based on a specific date range.
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The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
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The Python script assigns geographic values to the ‘Geo’ dimension at the campaign level based on specific keywords found in campaign names.
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The Python script calculates and manages pacing and budget allocation for advertising campaigns based on various metrics and goals.
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The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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Pace Daily Budget for each Strategy
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The Python script automates the tagging of campaigns as either “Brand” or “Generic” based on specific keywords in account and campaign names.
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Python script that looks for duplicate campaigns created by Dynamic Campaigns and sets the status to “Deleted” for any older campaigns.
Purpose: The Python script assigns corrected budget values at the campaign level to a dimension called “Meta ABO Budget” and labels campaigns as using ABO Budgets by setting the “Budget...
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The Python script processes campaign data to aggregate metrics like cost, clicks, and impressions over specified date ranges for each campaign, ensuring unique campaign entries.
Purpose
The Python script optimizes budget allocation for marketing campaigns to minimize lost impression share due to budget constraints.
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The Python script checks and filters campaigns based on their budget spending and status, ensuring they meet specific criteria for active traffic allocation.
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Python script to update campaign information based on specified conditions.
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The Python script identifies anomalies in campaign performance metrics for hotels by using day-of-week forecasts and calculating deviations based on user-defined thresholds.
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The Python script extracts and updates start and end dates from campaign names in a dataset, ensuring they are in a standardized format.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
The script extracts and updates specific campaign details from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script identifies duplicate keywords within the same publisher and account, recommends which keywords to pause based on performance metrics, and alerts users via email.
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The Python script calculates the remaining days for each campaign based on its start date and updates a CSV file with this information.
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The Python script updates a dataset to set the “Historical Quality Score - 1st of the month” dimension with the current quality score value for each keyword.
Purpose
Tag Brand vs Non Brand dimension automatically
Purpose
Parse out and populate Pacing - Start Date and Pacing - End Date in ISO format from the Campaign column of a DataFrame.
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The Python script assigns dimension values to campaigns based on their names, categorizing them as “Brand,” “Local,” or “Emergency.”
Purpose
Python script to detect anomalies in campaign data and generate an anomaly report.
Purpose
The Python script detects anomalies in campaign performance metrics for different campaign types and accounts.
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Analyze campaign data to identify anomalies and calculate anomaly scores for each product and account.
Purpose
Python script to tag ad groups if their CPA performance is abnormally high within a campaign.
Purpose
The Python script calculates the “Set Rate” for campaigns by aggregating six months of data, excluding the most recent 30 days, to account for latency.
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign
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The Python script automates budget adjustments for Bing campaigns by increasing the budget by 5% for campaigns that meet specific performance criteria over the past 30 days.
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The Python script automates the process of copying and updating Epicor monthly budgets from Google Sheets to a staging area at the start of each month.
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The Python script identifies and tags AdGroups with abnormally low Cost/Conversion performance within a campaign over a specified lookback period.
Purpose
Python script to pause and re-enable campaigns based on budget allocation.
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The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly assigned based on specific conditions.
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The Python script merges data from two sources, processes URLs, and prepares a structured output for further use.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly formatted based on specific conditions.
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The Python script processes and merges data from two sources to prepare a structured dataset for email marketing campaigns.
Purpose
Python script to auto-push a subset of suggested keywords from a keyword recommendations grid.
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The Python script processes marketing data to determine and populate the “NTB Uplift” dimension based on specific business conditions.
Purpose
Set dimensions based on campaign name.
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The Python script manages advertising campaigns by pausing them when the month-to-date (MTD) spend reaches the Epicor Monthly Budget, ensuring budget compliance.
Purpose
The script automates the process of setting all active Google Product Groups to Bid Override with no end date.
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The Python script identifies inactive campaigns based on publication costs and predicted user visits within a structured budget allocation framework.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR, Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance to previous 6 months.
Purpose
Tag Dimensions based on CRV, CPL, CPC, CTR performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
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The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
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The Python script updates the status, target CPA, and daily budget for new launch campaigns based on specified ROAS criteria.
Purpose:
The Python script automates the update of campaign statuses, bid strategies, and target CPA for new launch campaigns based on performance metrics.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize advertising campaigns.
Purpose:
The Python script updates the ‘Amazon Portfolio’ column in a DataFrame to match the ‘Portfolio’ column when discrepancies or null values are found.
Purpose:
The Python script updates the status, target cost-per-acquisition (tCPA), bid strategy, and maturity of new launch campaigns based on specified return on ad spend (ROAS) criteria.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose
This Python script is used to merge data from a primary data source and a reference data source, and then generate an output dataframe.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for email import, ensuring URLs are correctly formatted and assigned.
Purpose
Python script for media type tagging.
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The Python script categorizes media campaigns by tagging them with specific media types and sub-types based on predefined criteria.
Purpose:
The Python script categorizes media campaigns by assigning media types and subtypes based on specific keywords in the campaign data.
Purpose
Python script for tagging media types and subtypes in a dataset.
Purpose:
The Python script categorizes media types and sub-types based on specific keywords found in account, campaign, and group data.
Purpose:
The Python script categorizes media types and sub-types based on specific account and group criteria in a dataset.
Purpose:
The Python script categorizes media types and sub-types based on specific keywords found in account and campaign data.
Purpose:
The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months
Purpose
Python script to tag campaigns based on the comparison between the publisher cost and the daily budget.
Purpose
Tag Dimensions based on CVR, CPL, CPC, and CTR Performance compared to Preset Benchmarks
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The Python script is designed to clear the ‘Conversion Influencers’ dimension values in a dataset.
Purpose:
The Python script identifies and labels the top 10 keywords based on cost per conversion over the last 60 days, requiring at least one conversion to be considered.
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The Python script allocates daily budgets for each Epicor Budget Group by considering remaining budgets, weekdays, historical spending, and campaign activity.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
Purpose:
The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The script enforces monthly budget caps for advertising strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose:
The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
Purpose:
The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
Purpose:
The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
Purpose:
The script updates custom parameters for keywords with specific tags in the landing page result column.
Purpose
Python script for negative keyword expansion.
Purpose
Python script solves the problem of adjusting the Publisher Target ROAS for Google campaigns based on the daily spend goal and publisher cost.
Purpose:
The script updates custom parameters for keywords with specific tags in the landing page result column.
Purpose:
The Python script adjusts search bid values and bid override statuses for keywords in advertising campaigns based on specific performance criteria.
Purpose
Python script to assign campaign dimension values based on strategy/targeting type and campaign tactic.
Purpose:
The Python script assigns campaign dimension values based on specific patterns found in campaign names.
Purpose
Reduce the daily budget of campaigns by 20% if the GAAP profit from the previous day is less than 0.
Purpose:
The Python script assigns a specific campaign strategy and publisher strategy based on the current date matching the “CPA Date” in the data.
Purpose:
The Python script adjusts search bids for advertising campaigns based on specific criteria and conditions to optimize performance.
Purpose:
The Python script evaluates advertising campaigns to determine if they meet specific criteria for switching to a new publisher bidding strategy based on minimum ROAS and spend thresholds.
Purpose:
The script categorizes Yahoo DSP ad groups into ‘New’, ‘Mature I’, and ‘Mature II’ based on their spending over the previous 7 days.
Purpose:
The script adjusts the daily budget of campaigns by increasing it by 20% if the daily spend exceeds 60% of the current daily budget.
Purpose:
The Python script adjusts the “FullFunnel” strategy for marketing campaigns based on specific ratio criteria.
Purpose:
The Python script ensures that the SBA Pause Date remains within one month of the current date to allow the tool to unpause it.
Purpose
Pushes new Strategy Targets at start of month
Purpose:
The Python script processes marketing data to assign strategies based on performance metrics over specific time periods.
Purpose:
The Python script evaluates the pacing of campaigns against their structured budget allocation targets by analyzing conversion data.
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign
Purpose
Python script for tagging campaigns as “Brand” or “Non Brand” based on the campaign name.
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The Python script updates a DataFrame by copying yesterday’s cost data from one column to another.
Purpose:
The Python script updates a DataFrame by copying yesterday’s publication cost to a specific column for structured budget allocation purposes.
Purpose:
The Python script updates a DataFrame by copying yesterday’s publication cost into a specific column for structured budget allocation purposes.
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to populate the “Campaign Category” column in a DataFrame based on specific rules.
Purpose:
The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The Python script processes keyword data to manage and optimize advertising campaigns by pausing certain keywords based on performance metrics.
Purpose Python script that recommends changes to tROAS (target ROAS) and daily budget for Google Ads campaigns based on the performance of non-brand new customer ROAS over the last 30...
Purpose: The Python script ensures that the traffic dimension is consistently aligned across each bucket by setting all campaigns in a bucket to the maximum traffic value when one campaign...
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to add dimensions tag based on campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose
Python script to add dimensions tag based on campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose:
The script adjusts the target CPA and daily budget of Google campaigns based on recent ROAS and spending data.
Purpose:
The script identifies and pauses mature advertising campaigns with low Return on Ad Spend (ROAS) over the past 14 days.
Purpose:
The script assigns market identifiers to campaigns based on specific patterns in campaign names.
Purpose
The script adjusts the target cost-per-action (tCPA) for campaigns based on their current cost per conversion, increasing it if the cost is below a specified threshold.
Purpose:
The script checks if the “IB Last Updated” date is two or more days old and flags it for alert if certain conditions are met.
Purpose:
The Python script categorizes marketing campaigns into “Brand” or “Non-Brand” based on specific naming patterns.
Purpose:
The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘Mature’ based on their ROAS over the previous 14 days.
Purpose:
The Python script categorizes ExplorAds and Yahoo DSP campaigns into maturity labels based on their spending thresholds over the past year.
Purpose:
The Python script automates the process of pausing keywords and labeling them with the ‘AutoPause’ dimension based on specific criteria related to creation date, accumulated clicks, and spend.
Purpose:
The Python script automates the assignment of “Brand vs NonBrand” dimensions to campaigns based on their names.
Purpose:
The Python script automates the process of switching campaign publisher bidding strategies to Target CPA based on minimum spend and ROAS criteria.
Purpose:
The Python script automates the process of pausing new advertising campaigns with low Return on Advertising Spend (ROAS) based on predefined criteria.
Purpose
The script increases the daily budget for campaigns with an impression share greater than a specified percentage over the last specified number of days.
Purpose: The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘New Launch’ through ‘New - Round 5’ based on their ROAS over the past...
Purpose:
The Python script tags campaigns as ‘Brand’ or ‘Non-Brand’ based on the presence of the word ‘Brand’ in the campaign name.
Purpose:
The Python script categorizes campaigns into ‘Brand’ or ‘Non-Brand’ based on their names and outputs the results.
Purpose:
The Python script assigns a specific label to campaigns based on certain conditions in a dataset.
Purpose
Auto Pause After Event Date
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The script determines auction boost amounts for groups in specific campaigns based on various criteria, including pageviews, PUP scores, and shoot prices.
Purpose:
The script parses campaign names to extract and assign a tag based on a specific naming convention.
Purpose:
The Python script adjusts SBA targets by applying a target factor to raw targets.
Purpose
Reset Campaign Daily Budget by either 50% or pre-defined amount at start of each month.
Purpose: The Python script dynamically adjusts bid values for ad groups based on historical and target Return on Advertising Spend (ROAS) to optimize advertising strategies across clients in the Dutch...
Purpose
Clear Daily Winner and Overspend labels daily
Purpose
Tag AdGroup Dimensions per ROAS/CPA Performance
Purpose:
The Python script enforces monthly budget caps for strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose: The script automates the creation of suggested keywords from a keyword expansion report, focusing on long keywords with six or more tokens and setting them with specific attributes for...
Purpose:
The Python script identifies and tags campaigns with significantly lower Return on Advertising Spend (ROAS) compared to their peers within the same account.
Purpose:
The Python script identifies and tags AdGroups with abnormally low ROAS performance within a campaign over a specified lookback period.
Purpose:
The Python script reassigns advertising strategies to campaigns based on their Month-to-Date conversion levels.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose: The Python script adjusts campaign budgets by increasing them by 5% if the Cost Per Acquisition (CPA) performance is 10% better than the average of peers within the same...
Purpose: The Python script adjusts the budget of non-brand advertising campaigns by 5% if their cost-per-acquisition (CPA) performance is 10% better than the average of their peers within the same...
Purpose
Pause campaigns with no active groups.
Purpose:
The Python script identifies and tags AdGroups with a Cost Per Acquisition (CPA) significantly higher than their peers within the same campaign over a 30-day period.
Category Reference Datasource - None
Purpose:
The Python script automates the pausing and resuming of webinar ads based on their month-to-date (MTD) spending relative to a predefined monthly budget.
Purpose:
The Python script automates the pausing and reactivation of webinar creatives based on their cost, ensuring efficient budget management.
Purpose:
The Python script categorizes pacing percentages into descriptive tags such as “On Target” or “Over Pacing” based on predefined ranges.
Purpose:
The Python script extracts and updates GUIDs from campaign names in a dataset, ensuring only valid entries are retained.
Purpose:
The Python script dynamically allocates recommended daily budgets to campaigns based on input data.
Purpose:
The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget targets and current spending.
Purpose:
The Python script processes campaign data to update the status and paused date based on specific conditions.
Purpose:
The Python script adjusts revenue and conversion data at the keyword level based on latency factors to provide more accurate estimates.
Purpose:
The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds and generating a report for analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The script adjusts revenue and conversion data based on latency factors to provide more accurate estimates.
Purpose:
The Python script identifies outliers in campaign metrics and calculates anomalies using adjustable thresholds to generate a weekly report.
Purpose:
The script processes and tags dimensions in a dataset related to campaigns, publishers, and accounts.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script categorizes marketing campaigns into different strategies based on their Return on Advertising Spend (ROAS) performance.
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The script pauses ad groups with fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The Python script pauses ad groups with over 100 clicks that have not generated any Prime Starts/Conversions in the past 30 days, ensuring they have been active for at...
Purpose:
The Python script assigns a specific strategy to campaigns based on the account name when the strategy is initially unassigned.
Purpose:
The script pauses keywords with 0 conversions and 60+ clicks in the last 60 days, ensuring they have been active for at least 60 days.
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script processes account data to filter and transform it for structured budget allocation purposes.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script automates the process of updating daily budget allocations for advertising campaigns based on recommended values.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The script compares daily budget allocations to actual spending to assess pacing and budget status for advertising campaigns.
Purpose:
The Python script identifies and reports anomalies in monthly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The script extracts the country code from a group name by identifying the segment before the first hyphen.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The script extracts country codes and friendly names from campaign names in a dataset.
Purpose:
The Python script processes campaign data to extract and map program codes to their full names, filtering out entries where this mapping fails.
Purpose:
The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscore.
Purpose:
The Python script extracts the ‘REF Marker’ from the ‘Landing Page’ column and assigns it to the ‘REF Marker’ dimension in a structured data format.
Purpose:
The script extracts and processes Marketo IDs from campaign names in a dataset.
Purpose:
The Python script processes campaign data to extract and map program codes to their full names, creating a structured output for further analysis.
Purpose:
The script automatically labels campaign dimensions based on the campaign naming convention and campaign type.
Purpose:
The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscores.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The script extracts and tags the SFDC ID from campaign names in a dataset by identifying the value after the last ‘|’ character.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script calculates and adjusts bid modifications for different devices (mobile, tablet, desktop) based on CPA and ROAS strategy constraints for advertising campaigns.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script assigns a strategy name to each campaign by extracting it from a specific field in the campaign data.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes and summarizes the performance of marketing strategies by comparing actual results against targets, categorizing them based on management levels, and providing insights for optimization.
Purpose
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script processes marketing data to determine and populate the ‘NTB Uplift’ metric based on specific conditions related to revenue and new customer acquisition.
Purpose:
The Python script categorizes pacing percentages into descriptive tags such as ‘On Target’, ‘Under Pacing’, ‘Over Pacing’, etc., based on predefined ranges.
Purpose:
The Python script automatically maps advertising campaigns to specific strategies based on conversion rates and Return on Advertising Spend (ROAS) metrics over defined periods.
Purpose:
The script transfers Microsoft purchase conversion data into a new column labeled “Last365Days Conversions” within a dataset.
Purpose:
The script automates the process of pausing and reactivating advertising campaigns based on their daily budget utilization.
Purpose:
The Python script pauses keywords with more than 100 clicks and a cost per conversion above €2 for the last 7 days.
Purpose:
The Python script pauses keywords in a report that have between 10 and 100 clicks and a cost per conversion greater than €2.80 over the last 7 days.
Purpose:
The Python script pauses keywords with more than 10 clicks and a conversion rate below 10%.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script automates the pausing and re-enabling of advertising campaigns based on their monthly budget targets and current spending.
Purpose: The Python script manages campaign budgets by automatically pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget and re-enabling them when the spend falls below the budget....
Purpose
The Python script automates the process of allocating and updating daily budgets for advertising campaigns based on recommended values from a data source.
Purpose:
The Python script dynamically allocates and updates daily budgets for advertising campaigns based on recommended values.
Purpose:
The Python script extracts and tags the campaign strategy from the campaign name based on specific delimiters.
Purpose:
The script extracts and tags the numeric value before the first dash in a campaign name, removing any parentheses.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script dynamically allocates temporary traffic budgets based on recommended daily budgets from input data.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 33-day lookback period, excluding the most recent day.
Purpose:
The Python script tags campaigns based on their performance metrics compared to predefined benchmarks.
Purpose:
The Python script identifies duplicate keywords in advertising campaigns and recommends which ones to pause based on performance metrics.
Purpose:
The Python script identifies and recommends pausing keywords that are at least 30 days old, have zero conversions, and a quality score below 5.
Purpose:
The script qualifies suggested keywords based on conversion rates, CPA thresholds, and token count limits for effective ad targeting.
Purpose:
The Python script assigns a strategy to campaigns that are currently marked as ‘Unassigned’ based on a specific naming pattern.
Purpose:
The Python script adjusts daily budgets for advertising campaigns based on pacing cycles and specific criteria to optimize spending.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script automatically tags PS Clients based on specific keywords found in campaign names.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies weekly anomalies in campaign performance metrics using configurable thresholds and generates a summary report.
Purpose:
The Python script automatically tags manufacturer names based on keywords found in campaign names within a dataset.
Purpose: The Python script calculates the pacing of advertising strategies at the campaign level by comparing month-to-date spending against expected spending based on the total budget and elapsed days in...
Purpose:
The Python script calculates the adjusted daily budget for strategies at the campaign level based on remaining budget and days left in the month.
Purpose: The Python script identifies weekly anomalies in campaign performance metrics by analyzing outliers using configurable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a specified...
Purpose:
The Python script calculates predictive revenue values for campaigns using gross lead data and program-level revenue and conversion rates.
Purpose:
The Python script sets benchmarks for individual campaigns and strategies by analyzing performance metrics over specified time periods.
Purpose:
The Python script tags county codes to campaigns based on their names in a DataFrame.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose:
The Python script adjusts bid ratios for mobile, tablet, and desktop devices in advertising campaigns based on gross profit-weighted average bids.
Purpose:
The Python script transfers values from the “Portfolio” column to the “Amazon Portfolio” column in a dataset.
Purpose:
The Python script calculates the adjusted daily budget for various strategies based on remaining budget and days in the month.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script processes and transforms revenue data from various app store and subscription services to create a structured output for analysis.
Purpose:
The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
Purpose:
The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
Purpose
Automatically tags the “Product” dimension based on the product detail page URL of an ad.
Purpose:
The Python script identifies outliers in weekly campaign performance metrics using adjustable thresholds and generates a report accommodating conversion lag.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose: The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a configurable lookback...
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose
The script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies outliers in weekly campaign metrics using adjustable thresholds for anomaly detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script generates a weekly report to identify anomalies in campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script automatically tags marketing campaigns with a service dimension based on the campaign name.
Purpose:
The Python script tags product types based on campaign names in a DataFrame.
Purpose:
The script identifies and tags US states mentioned in the “Campaign” column of a DataFrame.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script detects and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The script ensures that any campaign with a daily budget below $50 is adjusted to meet this minimum threshold.
Purpose:
The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria within a dataset.
Purpose:
The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
Purpose:
The Python script sets a Target CPA Cap of $1000 for all active strategies or campaigns where the current CPA exceeds this limit.
Purpose:
The Python script identifies and analyzes anomalies in weekly campaign metrics to highlight outliers and trends for marketing performance evaluation.
Purpose:
The Python script clears existing dimension values to ensure only the top 20 keywords are labeled for the next day’s dimension script.
Purpose:
The Python script identifies and labels the top 10 performing keywords based on cost per conversion from a sorted report.
Purpose:
The script identifies and tags the top-performing keywords in a Google Ads report based on cost per conversion.
Purpose:
The Python script identifies and analyzes anomalies in weekly campaign performance metrics over the past eight weeks for Powpow Enterprise Retail.
Purpose:
The script processes and uploads daily budget data by transforming and deduplicating input records.
Purpose:
The script assigns dimension labels to campaigns based on their naming conventions and campaign types.
Purpose:
Automates the process of updating a remarketing dimension in a dataset based on specific campaign name values.
Purpose:
Automates the process of populating the brand dimension in a dataset based on specific rules applied to campaign name and type values.
Purpose:
Automates the categorization of campaigns by analyzing campaign names and assigning them to predefined categories.
Purpose:
Automates the process of populating device and match type dimensions in a dataset based on campaign name values.
Purpose:
Automates the process of populating subregion dimensions in a dataset based on campaign name values.
Purpose:
The script assigns the ‘Auto Pause Status’ of ‘traffic’ to new campaigns that are part of a strategy but have not yet been assigned this status.
Purpose:
The Python script categorizes PPC scores into letter grades ranging from A to D based on predefined score ranges.
Purpose:
Automates the process of updating UTM group dimensions based on ad group names by replacing spaces with plus signs.
Purpose:
Automates the population of utmcampaign and utmmedium dimensions based on campaign name and type.
Purpose:
The Python script processes and displays the initial rows of a primary data source for structured budget allocation workflows.
Purpose
The script automatically pauses campaigns in a dataset if their associated event dates have passed.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
The Python script processes keyword data to generate a structured keyword template based on specific group terms.
Purpose:
The Python script parses campaign names to extract and tag seminar details such as format, location, registration target, and seminar code.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on deviation levels.
Purpose:
The script parses campaign names to automatically tag hotel-related campaigns with specific Marin Dimensions tags, handling special cases for certain account names.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using adjustable thresholds.
Purpose:
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget specified in the strategy.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level by analyzing weekly data and applying statistical methods to detect outliers.
Purpose:
This Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on cost per conversion over the last 60 days for each school program.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level for a dental network by analyzing weekly performance data.
Purpose:
The Python script processes a DataFrame to extract and categorize information about campaigns, including studio names, feed categories, and language targets.
Purpose:
The Python script processes a DataFrame to extract and replace search phrases from keywords based on a given title, creating a new column with the modified keyword.
Purpose:
The Python script extracts a title from a “Group” column using a regex pattern and updates the “Title” column accordingly.
Purpose:
Automates the population of utmcampaign and utmmedium dimensions based on campaign name and campaign type values.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script calculates and tags campaigns with strategy-level benchmark scores for metrics such as MTD Gross Lead, CPL, CPL Trend, and Interview Rate.
Purpose
The script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script alerts users when the error rate in revenue processing files exceeds a specified threshold.
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The script identifies ads with expired or nearly expired application deadlines across all publishers.
Purpose: The Python script tags Meta Ads campaigns at the ad level based on performance metrics such as eCPM and CTR, categorizing them as “winning” or “losing” according to predefined...
Purpose:
The Python script tags Meta Ad Groups based on their performance metrics, categorizing them as “winning” or “losing” according to predefined business rules.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The script extracts and assigns a country code from a group name into a designated column based on specific parsing rules.
Purpose:
The script extracts and categorizes campaign types and game names from campaign names in a dataset.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script tags Meta campaign dimensions based on performance metrics to determine if they are “winning” or “losing.”
Purpose:
The script identifies and reports anomalies in weekly campaign conversions by analyzing deviations from forecasted metrics.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose:
The Python script identifies and recommends pausing keywords in advertising campaigns that are at least 30 days old, have zero conversions, and a quality score below 5.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose
The Python script identifies and reports on campaign performance anomalies by detecting outliers in key metrics using configurable thresholds and generates a weekly report accommodating conversion lag.
Purpose:
Matches the SBA Strategy Name and Targets to the Dynamic Allocation ones.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose: The Python script compares the CPA (Cost Per Acquisition) for campaigns between the current quarter and the last week, flagging those with a CPA for the last week that...
Purpose:
The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a dataset, ensuring it is reset to an empty state.
Purpose:
The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a data set, effectively resetting its values.
Purpose:
The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose:
The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose:
The script identifies and tags the top 10 keywords as “Top Performer” based on conversion count and cost per conversion over the last 60 days.
Purpose:
The Python script tags campaigns based on their performance metrics compared to predefined benchmarks, assigning tags like “Over Target,” “Under Target,” and “On Target.”
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
The script extracts the country code from a group name by identifying the segment before the first hyphen and assigns it to a ‘Country Code’ dimension.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
The script automates the extraction and tagging of the “Country Code” dimension from campaign names for Carburant’s Square Enix, excluding Meta publishers.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified latency model.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified formula.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion metrics and cost efficiency over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion and cost per conversion metrics over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 performing keywords based on conversion and cost per conversion over the last 60 days.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose
Python script that takes the unspent Strategy Spend Target from the previous month and adds it to the current Spend Target.
Purpose:
The Python script extracts and assigns a campaign type from campaign names based on a specific tag format.
Purpose:
The Python script extracts project numbers from campaign names by identifying tags that appear after a specified delimiter and assigns them to a designated dimension.
Purpose:
The script updates the ‘Campaign CPA This Quarter’ column with the current quarter’s CPA values for each campaign.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose
Python script to copy values from the ‘Strategy’ and ‘Strategy Target’ columns to the ‘SBA Strategy’ and ‘SBA Campaign Budget’ columns, respectively.
Purpose
Python script to pause campaigns when the monthly spend reaches the monthly budget stored in the strategy.
Purpose
Tag AdGroup if CPA performance is abnormally high within Campaign 30-lookback excluding recent 3 days
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script generates a performance anomaly report for pay-per-click marketing campaigns.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script processes campaign data to extract and categorize specific dimensions such as geo, segment, targeting, and platform from campaign names.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose:
The Python script processes campaign data to identify and tag audience and segment information based on predefined keywords.
Purpose:
The Python script identifies and tags geographical regions in campaign names based on predefined keywords.
Purpose:
The Python script processes campaign data to extract and tag platform and targeting information from campaign names.
Purpose:
The Python script extracts and categorizes geographical, segment, targeting, and platform information from campaign names in a dataset.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
Purpose:
The script extracts keyword match types from campaign names and updates a data frame accordingly.
Purpose:
The Python script identifies and tags the intent of marketing campaigns based on specific keywords found in campaign names.
Purpose:
The Python script processes campaign data to extract and assign topics based on a structured naming convention.
Purpose
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend approaches or exceeds the monthly budget set in a strategy.
Purpose:
The Python script manages the automatic pausing and re-enabling of advertising campaigns based on monthly budget targets defined in strategies.
Purpose
Python script to pause and resume campaigns based on monthly budget spend.
Purpose:
The Python script extracts and tags the “F-YY-Brand” from campaign names in a dataset, ensuring structured budget allocation.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose:
The script extracts and categorizes tags from non-brand campaign names in a dataset.
Purpose:
The Python script automates the process of calculating and adjusting daily budgets for marketing campaigns based on structured budget allocation (SBA) strategies.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
Purpose:
The script identifies campaigns with a significant discrepancy between the assigned “Two Year Cost (Publisher)” and the actual publisher cost over the last two years.
Purpose:
The Python script alerts the Program Manager when the percentage difference in a dataset is 15% or more, either positively or negatively.
Purpose
Campaigns Anomaly
Purpose:
Calculate the percentage difference between the current daily budget and the SBA recommended daily budget for campaigns.
Purpose
Python script to pause ad groups in select model-based new vehicle campaigns if there are 3 or fewer vehicles in stock.
Purpose:
Automatically tags marketing campaigns as either Brand or NonBrand based on their names.
Purpose
Automating Dimension Tagging with the landing page in the dimension “Landing Page Dim” and the keyword and match type combination in the dimension “Keyword MatchType Dim”.
Purpose
Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for Category.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for campaign type.
Purpose
Campaign Performance Anomaly Report with Summary
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automatically assigns a campaign to a specific bidding strategy based on the campaign’s age.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script to add a tag to a campaign name based on a specified separator.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script updates the “Keyword Cost/Conv Performance” dimension for keywords whose cost per conversion is 30% greater than their campaign’s cost per conversion.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and remaining weekdays in the month.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script updates the “Campaign 30 Day Cost per Conversion” dimension daily to support keyword-level anomaly detection for cost per conversion.
Purpose
Pause Poor performing Keywords with 0 Conv. and QS <5
Purpose:
The Python script identifies and tags campaigns where the previous day’s spending is at least 90% of the daily budget and certain conditions are met.
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies and tags campaigns where the publisher cost for the prior day is at least 90% of the daily budget, indicating a potential budget cap situation....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the publisher cost for the prior day is at least 90% of the daily budget and flags them as “Budget Capped.”
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the previous day’s spending was at least 90% of the daily budget and flags them if certain conditions are met.
Purpose: The Python script identifies campaigns where the previous day’s spending is at least 90% of the daily budget and flags them as “Budget Capped” if certain conditions are met....
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
Parse Campaign Name and add Campaign-level Marin Dimensions Tag for Placement.
Purpose
Campaign Performance Anomaly Report with Summary
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds for interquartile range and deviation.
Purpose
Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script identifies keywords with duplicate MKWID values and prepares them for reupload with blank custom parameters.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and potential spend.
Purpose
Auto Tag Campaign with Tipo de Campanha Dimension
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
Automatically tags campaigns with ‘Brand’ or ‘NonBrand’ based on specific keywords in the campaign name.
Purpose
Auto Tag the funnel stage of campaigns based on the campaign name.
Purpose:
The Python script generates negative keywords for single keyword campaigns by cross-negating keywords within each account.
Purpose:
Calculates the difference between SBA allocation and the percentage of total publication cost.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
Purpose:
The Python script identifies and reports campaign-level outliers in key conversion metrics, such as Total AMU Sign-Ups and Podcast First Stream, by calculating anomalies using adjustable thresholds.
Purpose: The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by calculating recommended daily budgets based on historical spend, remaining budget, and pacing...
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that pauses and re-enables campaigns based on their monthly spend and budget.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose:
The Python script extracts specific information from campaign names and organizes it into a structured format for further analysis.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose:
The Python script calculates pacing metrics and recommended daily budgets for digital advertising campaigns based on various campaign parameters and goals.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and calculating deviations using adjustable thresholds.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Remove the dollar sign ($) from the SBA Campaign Budget column in a given input dataframe.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script solves the problem of calculating various metrics and values for a campaign, such as total pub cost, total impressions, total clicks, total views, pacing cycle start...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The script pauses advertisements if they have zero conversions after spending $100.
Purpose
Pauses ads that have a CPA of $150+ over the previous 7 days
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their goals within specified timeframes.
Purpose:
The Python script automates the process of setting dimensions based on campaign names for marketing campaigns.
Purpose:
The script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets for Google Smart Bidding strategies.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
Purpose:
The script calculates and stores the average cost-per-click (CPC) for the last 28 days in a specified dimension called “Test.”
Purpose:
The Python script identifies performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets, specifically supporting Google Smart Bidding strategies.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose Python script that solves the problem of allocating budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget....
Purpose The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and rolling up performance metrics to dimensions such as Product Category and Brand/Generic, using adjustable IQR and...
Purpose:
The Python script identifies ad groups within campaigns that have abnormally high Cost Per Acquisition (CPA) performance, tagging them as outliers.
Purpose:
The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script detects performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts derived from historical trends.
Purpose
Campaign Anomaly Detection
Purpose
Python script solves the problem of generating a performance anomaly report for pay-per-click marketing data.
Purpose
The Python script automatically pauses or resumes marketing campaigns based on their month-to-date (MTD) spending relative to a predefined budget cap.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation (SBA) processes.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The script automatically tags campaigns as “Brand” or “Non-Brand” based on the campaign name, specifically tagging as “Non-Brand” if the name starts with ‘EEE’.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script automates the process of tagging campaigns with combined school and program dimensions and assigns an SBA strategy based on these tags.
Purpose
Python script that combines the ‘School’ and ‘Program’ columns into a new column called ‘School_Program’ and assigns the created tag to the ‘School_Program’ column.
Purpose:
The script parses campaign names to automatically tag them with a program identifier based on a specific naming convention.
Purpose:
The Python script parses campaign names to automatically tag them with a school dimension based on the text before the first underscore.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script optimizes budget allocation for advertising campaigns to minimize lost impression share due to budget constraints.
Purpose:
The script parses campaign names to automatically tag them with a region-specific dimension based on predefined rules.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose
This Python script solves the problem of calculating various metrics and values for pacing and budget allocation in a digital advertising campaign.
Purpose:
The Python script is designed to optimize daily budget allocation for Search SBA strategies by minimizing lost impression share due to budget constraints.
Purpose:
The script assigns Meta ABO Budget values at the group level for active Meta Ad sets, removing any previously assigned values at the campaign level.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose:
The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose:
The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
Purpose:
The Python script monitors campaign spending and recommends pausing campaigns if projected costs exceed the monthly budget.
Purpose
SBA Campaigns Watcher
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script assigns geographic values to the ‘Geo’ dimension at the campaign level based on specific keywords found in campaign names.
Purpose:
The Python script calculates and manages pacing and budget allocation for advertising campaigns based on various metrics and goals.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose
Pace Daily Budget for each Strategy
Purpose:
The Python script automates the tagging of campaigns as either “Brand” or “Generic” based on specific keywords in account and campaign names.
Purpose
Python script that looks for duplicate campaigns created by Dynamic Campaigns and sets the status to “Deleted” for any older campaigns.
Purpose: The Python script assigns corrected budget values at the campaign level to a dimension called “Meta ABO Budget” and labels campaigns as using ABO Budgets by setting the “Budget...
Purpose:
The Python script processes campaign data to aggregate metrics like cost, clicks, and impressions over specified date ranges for each campaign, ensuring unique campaign entries.
Purpose
The Python script optimizes budget allocation for marketing campaigns to minimize lost impression share due to budget constraints.
Purpose:
The Python script checks and filters campaigns based on their budget spending and status, ensuring they meet specific criteria for active traffic allocation.
Purpose
Python script to update campaign information based on specified conditions.
Purpose:
The Python script identifies anomalies in campaign performance metrics for hotels by using day-of-week forecasts and calculating deviations based on user-defined thresholds.
Purpose:
The Python script extracts and updates start and end dates from campaign names in a dataset, ensuring they are in a standardized format.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
The script extracts and updates specific campaign details from campaign names in a dataset.
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The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script identifies duplicate keywords within the same publisher and account, recommends which keywords to pause based on performance metrics, and alerts users via email.
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The Python script calculates the remaining days for each campaign based on its start date and updates a CSV file with this information.
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The Python script updates a dataset to set the “Historical Quality Score - 1st of the month” dimension with the current quality score value for each keyword.
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Tag Brand vs Non Brand dimension automatically
Purpose
Parse out and populate Pacing - Start Date and Pacing - End Date in ISO format from the Campaign column of a DataFrame.
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The Python script assigns dimension values to campaigns based on their names, categorizing them as “Brand,” “Local,” or “Emergency.”
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Python script to detect anomalies in campaign data and generate an anomaly report.
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The Python script detects anomalies in campaign performance metrics for different campaign types and accounts.
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Analyze campaign data to identify anomalies and calculate anomaly scores for each product and account.
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Python script to tag ad groups if their CPA performance is abnormally high within a campaign.
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The Python script calculates the “Set Rate” for campaigns by aggregating six months of data, excluding the most recent 30 days, to account for latency.
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Tag AdGroup if CPA performance is abnormally high within Campaign
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The Python script automates budget adjustments for Bing campaigns by increasing the budget by 5% for campaigns that meet specific performance criteria over the past 30 days.
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The Python script identifies and tags AdGroups with abnormally low Cost/Conversion performance within a campaign over a specified lookback period.
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Python script to pause and re-enable campaigns based on budget allocation.
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Python script to auto-push a subset of suggested keywords from a keyword recommendations grid.
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The Python script processes marketing data to determine and populate the “NTB Uplift” dimension based on specific business conditions.
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Set dimensions based on campaign name.
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The Python script manages advertising campaigns by pausing them when the month-to-date (MTD) spend reaches the Epicor Monthly Budget, ensuring budget compliance.
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The script automates the process of setting all active Google Product Groups to Bid Override with no end date.
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The Python script identifies inactive campaigns based on publication costs and predicted user visits within a structured budget allocation framework.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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Tag Dimensions based on CVR, CPL, CPC, CTR, Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance to previous 6 months.
Purpose
Tag Dimensions based on CRV, CPL, CPC, CTR performance compared to previous 6 months.
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Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
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The Python script updates the status, target CPA, and daily budget for new launch campaigns based on specified ROAS criteria.
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The Python script automates the update of campaign statuses, bid strategies, and target CPA for new launch campaigns based on performance metrics.
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Python script to tag campaigns based on their performance metrics compared to benchmarks.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
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The Python script adjusts keyword headroom based on historical performance data to optimize advertising campaigns.
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The Python script updates the ‘Amazon Portfolio’ column in a DataFrame to match the ‘Portfolio’ column when discrepancies or null values are found.
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The Python script updates the status, target cost-per-acquisition (tCPA), bid strategy, and maturity of new launch campaigns based on specified return on ad spend (ROAS) criteria.
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The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
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Python script for media type tagging.
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The Python script categorizes media campaigns by tagging them with specific media types and sub-types based on predefined criteria.
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The Python script categorizes media campaigns by assigning media types and subtypes based on specific keywords in the campaign data.
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Python script for tagging media types and subtypes in a dataset.
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The Python script categorizes media types and sub-types based on specific keywords found in account, campaign, and group data.
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The Python script categorizes media types and sub-types based on specific account and group criteria in a dataset.
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The Python script categorizes media types and sub-types based on specific keywords found in account and campaign data.
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The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
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Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months
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Python script to tag campaigns based on the comparison between the publisher cost and the daily budget.
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Tag Dimensions based on CVR, CPL, CPC, and CTR Performance compared to Preset Benchmarks
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The Python script is designed to clear the ‘Conversion Influencers’ dimension values in a dataset.
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The Python script identifies and labels the top 10 keywords based on cost per conversion over the last 60 days, requiring at least one conversion to be considered.
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The Python script allocates daily budgets for each Epicor Budget Group by considering remaining budgets, weekdays, historical spending, and campaign activity.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
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The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
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The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
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The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
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The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
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The script updates custom parameters for keywords with specific tags in the landing page result column.
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Python script for negative keyword expansion.
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Python script solves the problem of adjusting the Publisher Target ROAS for Google campaigns based on the daily spend goal and publisher cost.
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The script updates custom parameters for keywords with specific tags in the landing page result column.
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The Python script adjusts search bid values and bid override statuses for keywords in advertising campaigns based on specific performance criteria.
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Python script to assign campaign dimension values based on strategy/targeting type and campaign tactic.
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The Python script assigns campaign dimension values based on specific patterns found in campaign names.
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Reduce the daily budget of campaigns by 20% if the GAAP profit from the previous day is less than 0.
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The Python script assigns a specific campaign strategy and publisher strategy based on the current date matching the “CPA Date” in the data.
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The Python script adjusts search bids for advertising campaigns based on specific criteria and conditions to optimize performance.
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The Python script evaluates advertising campaigns to determine if they meet specific criteria for switching to a new publisher bidding strategy based on minimum ROAS and spend thresholds.
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The script categorizes Yahoo DSP ad groups into ‘New’, ‘Mature I’, and ‘Mature II’ based on their spending over the previous 7 days.
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The script adjusts the daily budget of campaigns by increasing it by 20% if the daily spend exceeds 60% of the current daily budget.
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The Python script adjusts the “FullFunnel” strategy for marketing campaigns based on specific ratio criteria.
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The Python script ensures that the SBA Pause Date remains within one month of the current date to allow the tool to unpause it.
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Pushes new Strategy Targets at start of month
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The Python script processes marketing data to assign strategies based on performance metrics over specific time periods.
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The Python script evaluates the pacing of campaigns against their structured budget allocation targets by analyzing conversion data.
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Tag AdGroup if CPA performance is abnormally high within Campaign
Purpose
Python script for tagging campaigns as “Brand” or “Non Brand” based on the campaign name.
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The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
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The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
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The Python script updates a DataFrame by copying yesterday’s cost data from one column to another.
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The Python script updates a DataFrame by copying yesterday’s publication cost to a specific column for structured budget allocation purposes.
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The Python script updates a DataFrame by copying yesterday’s publication cost into a specific column for structured budget allocation purposes.
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The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to populate the “Campaign Category” column in a DataFrame based on specific rules.
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The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
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The Python script processes keyword data to manage and optimize advertising campaigns by pausing certain keywords based on performance metrics.
Purpose Python script that recommends changes to tROAS (target ROAS) and daily budget for Google Ads campaigns based on the performance of non-brand new customer ROAS over the last 30...
Purpose: The Python script ensures that the traffic dimension is consistently aligned across each bucket by setting all campaigns in a bucket to the maximum traffic value when one campaign...
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to add dimensions tag based on campaign name.
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Python script to add a dimensions tag based on the campaign name.
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Python script to add dimensions tag based on campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
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Python script to add a dimensions tag based on the campaign name.
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The script adjusts the target CPA and daily budget of Google campaigns based on recent ROAS and spending data.
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The script identifies and pauses mature advertising campaigns with low Return on Ad Spend (ROAS) over the past 14 days.
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The script assigns market identifiers to campaigns based on specific patterns in campaign names.
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The script adjusts the target cost-per-action (tCPA) for campaigns based on their current cost per conversion, increasing it if the cost is below a specified threshold.
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The script checks if the “IB Last Updated” date is two or more days old and flags it for alert if certain conditions are met.
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The Python script categorizes marketing campaigns into “Brand” or “Non-Brand” based on specific naming patterns.
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The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘Mature’ based on their ROAS over the previous 14 days.
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The Python script categorizes ExplorAds and Yahoo DSP campaigns into maturity labels based on their spending thresholds over the past year.
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The Python script automates the process of pausing keywords and labeling them with the ‘AutoPause’ dimension based on specific criteria related to creation date, accumulated clicks, and spend.
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The Python script automates the assignment of “Brand vs NonBrand” dimensions to campaigns based on their names.
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The Python script automates the process of switching campaign publisher bidding strategies to Target CPA based on minimum spend and ROAS criteria.
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The Python script automates the process of pausing new advertising campaigns with low Return on Advertising Spend (ROAS) based on predefined criteria.
Purpose
The script increases the daily budget for campaigns with an impression share greater than a specified percentage over the last specified number of days.
Purpose: The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘New Launch’ through ‘New - Round 5’ based on their ROAS over the past...
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The Python script tags campaigns as ‘Brand’ or ‘Non-Brand’ based on the presence of the word ‘Brand’ in the campaign name.
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The Python script categorizes campaigns into ‘Brand’ or ‘Non-Brand’ based on their names and outputs the results.
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The Python script assigns a specific label to campaigns based on certain conditions in a dataset.
Purpose
Auto Pause After Event Date
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The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
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The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
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The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
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The script determines auction boost amounts for groups in specific campaigns based on various criteria, including pageviews, PUP scores, and shoot prices.
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The script parses campaign names to extract and assign a tag based on a specific naming convention.
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The Python script adjusts SBA targets by applying a target factor to raw targets.
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Reset Campaign Daily Budget by either 50% or pre-defined amount at start of each month.
Purpose: The Python script dynamically adjusts bid values for ad groups based on historical and target Return on Advertising Spend (ROAS) to optimize advertising strategies across clients in the Dutch...
Purpose
Clear Daily Winner and Overspend labels daily
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Tag AdGroup Dimensions per ROAS/CPA Performance
Purpose: The script automates the creation of suggested keywords from a keyword expansion report, focusing on long keywords with six or more tokens and setting them with specific attributes for...
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The Python script identifies and tags campaigns with significantly lower Return on Advertising Spend (ROAS) compared to their peers within the same account.
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The Python script identifies and tags AdGroups with abnormally low ROAS performance within a campaign over a specified lookback period.
Purpose:
The Python script reassigns advertising strategies to campaigns based on their Month-to-Date conversion levels.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose: The Python script adjusts campaign budgets by increasing them by 5% if the Cost Per Acquisition (CPA) performance is 10% better than the average of peers within the same...
Purpose: The Python script adjusts the budget of non-brand advertising campaigns by 5% if their cost-per-acquisition (CPA) performance is 10% better than the average of their peers within the same...
Purpose
Pause campaigns with no active groups.
Purpose:
The Python script identifies and tags AdGroups with a Cost Per Acquisition (CPA) significantly higher than their peers within the same campaign over a 30-day period.
Category Item Changed - Campaign
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
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The Python script categorizes pacing percentages into descriptive tags such as “On Target” or “Over Pacing” based on predefined ranges.
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The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
Purpose:
The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
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The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
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The Python script extracts and updates GUIDs from campaign names in a dataset, ensuring only valid entries are retained.
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The Python script dynamically allocates recommended daily budgets to campaigns based on input data.
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The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
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The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget targets and current spending.
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The Python script processes campaign data to update the status and paused date based on specific conditions.
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The script processes and tags dimensions in a dataset related to campaigns, publishers, and accounts.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
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The Python script categorizes marketing campaigns into different strategies based on their Return on Advertising Spend (ROAS) performance.
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The Python script assigns a specific strategy to campaigns based on the account name when the strategy is initially unassigned.
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The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script automates the process of updating daily budget allocations for advertising campaigns based on recommended values.
Purpose:
The script compares daily budget allocations to actual spending to assess pacing and budget status for advertising campaigns.
Purpose
The script processes and merges campaign budget data from a primary data source and Google Sheets to update daily budgets for campaigns.
Purpose
The Python script maps Salesforce (SFDC) input data to a structured format for further analysis and reporting.
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The script extracts country codes and friendly names from campaign names in a dataset.
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The Python script processes campaign data to extract and map program codes to their full names, filtering out entries where this mapping fails.
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The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscore.
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The script extracts and processes Marketo IDs from campaign names in a dataset.
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The Python script processes campaign data to extract and map program codes to their full names, creating a structured output for further analysis.
Purpose:
The script automatically labels campaign dimensions based on the campaign naming convention and campaign type.
Purpose:
The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscores.
Purpose:
The script extracts and tags the SFDC ID from campaign names in a dataset by identifying the value after the last ‘|’ character.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
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The Python script assigns a strategy name to each campaign by extracting it from a specific field in the campaign data.
Purpose:
The Python script categorizes pacing percentages into descriptive tags such as ‘On Target’, ‘Under Pacing’, ‘Over Pacing’, etc., based on predefined ranges.
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The Python script automatically maps advertising campaigns to specific strategies based on conversion rates and Return on Advertising Spend (ROAS) metrics over defined periods.
Purpose:
The script transfers Microsoft purchase conversion data into a new column labeled “Last365Days Conversions” within a dataset.
Purpose:
The script automates the process of setting daily budgets for campaigns by merging data from a primary data source with a Google Sheets reference.
Purpose:
The script automates the process of pausing and reactivating advertising campaigns based on their daily budget utilization.
Purpose:
The Python script automates the pausing and re-enabling of advertising campaigns based on their monthly budget targets and current spending.
Purpose: The Python script manages campaign budgets by automatically pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget and re-enabling them when the spend falls below the budget....
Purpose
The Python script automates the process of allocating and updating daily budgets for advertising campaigns based on recommended values from a data source.
Purpose:
The Python script dynamically allocates and updates daily budgets for advertising campaigns based on recommended values.
Purpose:
The Python script extracts and tags the campaign strategy from the campaign name based on specific delimiters.
Purpose:
The script extracts and tags the numeric value before the first dash in a campaign name, removing any parentheses.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script dynamically allocates temporary traffic budgets based on recommended daily budgets from input data.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script tags campaigns based on their performance metrics compared to predefined benchmarks.
Purpose:
The Python script assigns a strategy to campaigns that are currently marked as ‘Unassigned’ based on a specific naming pattern.
Purpose:
The Python script processes and merges campaign budget data from a primary data source and a Google Sheets reference to prepare a structured budget allocation for campaigns.
Purpose:
The Python script adjusts daily budgets for advertising campaigns based on pacing cycles and specific criteria to optimize spending.
Purpose:
The Python script automatically tags PS Clients based on specific keywords found in campaign names.
Purpose:
The Python script automatically tags manufacturer names based on keywords found in campaign names within a dataset.
Purpose: The Python script calculates the pacing of advertising strategies at the campaign level by comparing month-to-date spending against expected spending based on the total budget and elapsed days in...
Purpose:
The Python script calculates the adjusted daily budget for strategies at the campaign level based on remaining budget and days left in the month.
Purpose:
The Python script sets benchmarks for individual campaigns and strategies by analyzing performance metrics over specified time periods.
Purpose:
The Python script tags county codes to campaigns based on their names in a DataFrame.
Purpose:
The Python script transfers values from the “Portfolio” column to the “Amazon Portfolio” column in a dataset.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script synchronizes campaign budget data from a primary data source with updates from a Google Sheets reference, ensuring daily budget allocations are current.
Purpose:
The Python script automatically tags marketing campaigns with a service dimension based on the campaign name.
Purpose:
The Python script tags product types based on campaign names in a DataFrame.
Purpose:
The script identifies and tags US states mentioned in the “Campaign” column of a DataFrame.
Purpose:
The script ensures that any campaign with a daily budget below $50 is adjusted to meet this minimum threshold.
Purpose:
The Python script sets a Target CPA Cap of $1000 for all active strategies or campaigns where the current CPA exceeds this limit.
Purpose:
The script assigns dimension labels to campaigns based on their naming conventions and campaign types.
Purpose:
Automates the process of updating a remarketing dimension in a dataset based on specific campaign name values.
Purpose:
Automates the process of populating the brand dimension in a dataset based on specific rules applied to campaign name and type values.
Purpose:
Automates the categorization of campaigns by analyzing campaign names and assigning them to predefined categories.
Purpose:
Automates the process of populating device and match type dimensions in a dataset based on campaign name values.
Purpose:
Automates the process of populating subregion dimensions in a dataset based on campaign name values.
Purpose:
The script assigns the ‘Auto Pause Status’ of ‘traffic’ to new campaigns that are part of a strategy but have not yet been assigned this status.
Purpose:
The Python script categorizes PPC scores into letter grades ranging from A to D based on predefined score ranges.
Purpose:
Automates the population of utmcampaign and utmmedium dimensions based on campaign name and type.
Purpose:
The Python script processes and displays the initial rows of a primary data source for structured budget allocation workflows.
Purpose:
The Python script parses campaign names to extract and tag seminar details such as format, location, registration target, and seminar code.
Purpose:
The Python script automates the process of enabling a campaign override flag when adjusted recommendations exceed predefined caps set in Google Sheets.
Purpose:
The script parses campaign names to automatically tag hotel-related campaigns with specific Marin Dimensions tags, handling special cases for certain account names.
Purpose:
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget specified in the strategy.
Purpose:
The Python script processes a DataFrame to extract and categorize information about campaigns, including studio names, feed categories, and language targets.
Purpose:
The Python script updates benchmark dimensions in Marin by copying data from a staging Google Sheet, matching the ‘Abbreviation’ column with the ‘Strategy’ column.
Purpose:
Automates the population of utmcampaign and utmmedium dimensions based on campaign name and campaign type values.
Purpose:
The Python script calculates and tags campaigns with strategy-level benchmark scores for metrics such as MTD Gross Lead, CPL, CPL Trend, and Interview Rate.
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The script extracts and categorizes campaign types and game names from campaign names in a dataset.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script tags Meta campaign dimensions based on performance metrics to determine if they are “winning” or “losing.”
Purpose:
Matches the SBA Strategy Name and Targets to the Dynamic Allocation ones.
Purpose:
The Python script tags campaigns based on their performance metrics compared to predefined benchmarks, assigning tags like “Over Target,” “Under Target,” and “On Target.”
Purpose
The script automates the extraction and tagging of the “Country Code” dimension from campaign names for Carburant’s Square Enix, excluding Meta publishers.
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The Python script extracts and assigns a campaign type from campaign names based on a specific tag format.
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The Python script extracts project numbers from campaign names by identifying tags that appear after a specified delimiter and assigns them to a designated dimension.
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The script updates the ‘Campaign CPA This Quarter’ column with the current quarter’s CPA values for each campaign.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose
Python script to copy values from the ‘Strategy’ and ‘Strategy Target’ columns to the ‘SBA Strategy’ and ‘SBA Campaign Budget’ columns, respectively.
Purpose
Python script to pause campaigns when the monthly spend reaches the monthly budget stored in the strategy.
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The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script automates the process of tagging campaigns with the appropriate program manager based on data from Google Sheets.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
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The Python script processes campaign data to extract and categorize specific dimensions such as geo, segment, targeting, and platform from campaign names.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose:
The Python script processes campaign data to identify and tag audience and segment information based on predefined keywords.
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The Python script identifies and tags geographical regions in campaign names based on predefined keywords.
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The Python script processes campaign data to extract and tag platform and targeting information from campaign names.
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The Python script extracts and categorizes geographical, segment, targeting, and platform information from campaign names in a dataset.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
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The script extracts keyword match types from campaign names and updates a data frame accordingly.
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The Python script identifies and tags the intent of marketing campaigns based on specific keywords found in campaign names.
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The Python script processes campaign data to extract and assign topics based on a structured naming convention.
Purpose
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend approaches or exceeds the monthly budget set in a strategy.
Purpose:
The Python script manages the automatic pausing and re-enabling of advertising campaigns based on monthly budget targets defined in strategies.
Purpose
Python script to pause and resume campaigns based on monthly budget spend.
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The Python script extracts and tags the “F-YY-Brand” from campaign names in a dataset, ensuring structured budget allocation.
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The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
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The script extracts and categorizes tags from non-brand campaign names in a dataset.
Purpose:
The Python script automates the process of calculating and adjusting daily budgets for marketing campaigns based on structured budget allocation (SBA) strategies.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
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The script identifies campaigns with a significant discrepancy between the assigned “Two Year Cost (Publisher)” and the actual publisher cost over the last two years.
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The Python script alerts the Program Manager when the percentage difference in a dataset is 15% or more, either positively or negatively.
Purpose:
Calculate the percentage difference between the current daily budget and the SBA recommended daily budget for campaigns.
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Automatically tags marketing campaigns as either Brand or NonBrand based on their names.
Purpose
Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for Category.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for campaign type.
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The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
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The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automatically assigns a campaign to a specific bidding strategy based on the campaign’s age.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
Purpose
Python script to add a tag to a campaign name based on a specified separator.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and remaining weekdays in the month.
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The Python script updates the “Campaign 30 Day Cost per Conversion” dimension daily to support keyword-level anomaly detection for cost per conversion.
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The Python script identifies and tags campaigns where the previous day’s spending is at least 90% of the daily budget and certain conditions are met.
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies and tags campaigns where the publisher cost for the prior day is at least 90% of the daily budget, indicating a potential budget cap situation....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the publisher cost for the prior day is at least 90% of the daily budget and flags them as “Budget Capped.”
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the previous day’s spending was at least 90% of the daily budget and flags them if certain conditions are met.
Purpose: The Python script identifies campaigns where the previous day’s spending is at least 90% of the daily budget and flags them as “Budget Capped” if certain conditions are met....
Purpose
Parse Campaign Name and add Campaign-level Marin Dimensions Tag for Placement.
Purpose
Python script to pause and resume campaigns based on Dimension tags (SBA Strategy and SBA Monthly Budget) by monitoring bi-hourly intraday spend.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and potential spend.
Purpose
Auto Tag Campaign with Tipo de Campanha Dimension
Purpose
Automatically tags campaigns with ‘Brand’ or ‘NonBrand’ based on specific keywords in the campaign name.
Purpose
Auto Tag the funnel stage of campaigns based on the campaign name.
Purpose:
Calculates the difference between SBA allocation and the percentage of total publication cost.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
Purpose:
The Python script automates the process of copying and updating monthly budget allocations from Google Sheets to a structured budget allocation system by matching campaign strategies.
Purpose: The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by calculating recommended daily budgets based on historical spend, remaining budget, and pacing...
Purpose
Python script that pauses and re-enables campaigns based on their monthly spend and budget.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose:
The Python script extracts specific information from campaign names and organizes it into a structured format for further analysis.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose:
The Python script calculates pacing metrics and recommended daily budgets for digital advertising campaigns based on various campaign parameters and goals.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
Remove the dollar sign ($) from the SBA Campaign Budget column in a given input dataframe.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
Python script to filter and process campaign data based on specific criteria.
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The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns, ensuring they meet their budget and performance goals.
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script solves the problem of calculating various metrics and values for a campaign, such as total pub cost, total impressions, total clicks, total views, pacing cycle start...
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their goals within specified timeframes.
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The Python script automates the process of setting dimensions based on campaign names for marketing campaigns.
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The script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets for Google Smart Bidding strategies.
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The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
Purpose:
The script calculates and stores the average cost-per-click (CPC) for the last 28 days in a specified dimension called “Test.”
Purpose:
The Python script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets, specifically supporting Google Smart Bidding strategies.
Purpose:
The Python script automates the process of pausing and resuming advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose Python script that solves the problem of allocating budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget....
Purpose:
The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose
The Python script automatically pauses or resumes marketing campaigns based on their month-to-date (MTD) spending relative to a predefined budget cap.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation (SBA) processes.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The script automatically tags campaigns as “Brand” or “Non-Brand” based on the campaign name, specifically tagging as “Non-Brand” if the name starts with ‘EEE’.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script automates the process of tagging campaigns with combined school and program dimensions and assigns an SBA strategy based on these tags.
Purpose
Python script that combines the ‘School’ and ‘Program’ columns into a new column called ‘School_Program’ and assigns the created tag to the ‘School_Program’ column.
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The script parses campaign names to automatically tag them with a program identifier based on a specific naming convention.
Purpose:
The Python script parses campaign names to automatically tag them with a school dimension based on the text before the first underscore.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script optimizes budget allocation for advertising campaigns to minimize lost impression share due to budget constraints.
Purpose:
The script parses campaign names to automatically tag them with a region-specific dimension based on predefined rules.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose
This Python script solves the problem of calculating various metrics and values for pacing and budget allocation in a digital advertising campaign.
Purpose:
The Python script is designed to optimize daily budget allocation for Search SBA strategies by minimizing lost impression share due to budget constraints.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose:
The Python script monitors campaign spending and recommends pausing campaigns if projected costs exceed the monthly budget.
Purpose
SBA Campaigns Watcher
Purpose:
The Python script assigns geographic values to the ‘Geo’ dimension at the campaign level based on specific keywords found in campaign names.
Purpose:
The Python script calculates and manages pacing and budget allocation for advertising campaigns based on various metrics and goals.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose
Pace Daily Budget for each Strategy
Purpose:
The Python script automates the tagging of campaigns as either “Brand” or “Generic” based on specific keywords in account and campaign names.
Purpose
Python script that looks for duplicate campaigns created by Dynamic Campaigns and sets the status to “Deleted” for any older campaigns.
Purpose: The Python script assigns corrected budget values at the campaign level to a dimension called “Meta ABO Budget” and labels campaigns as using ABO Budgets by setting the “Budget...
Purpose:
The Python script processes campaign data to aggregate metrics like cost, clicks, and impressions over specified date ranges for each campaign, ensuring unique campaign entries.
Purpose
The Python script optimizes budget allocation for marketing campaigns to minimize lost impression share due to budget constraints.
Purpose
Python script to update campaign information based on specified conditions.
Purpose:
The Python script extracts and updates start and end dates from campaign names in a dataset, ensuring they are in a standardized format.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
The script extracts and updates specific campaign details from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script calculates the remaining days for each campaign based on its start date and updates a CSV file with this information.
Purpose
Tag Brand vs Non Brand dimension automatically
Purpose
Parse out and populate Pacing - Start Date and Pacing - End Date in ISO format from the Campaign column of a DataFrame.
Purpose:
The Python script assigns dimension values to campaigns based on their names, categorizing them as “Brand,” “Local,” or “Emergency.”
Purpose
The Python script calculates the “Set Rate” for campaigns by aggregating six months of data, excluding the most recent 30 days, to account for latency.
Purpose:
The Python script automates budget adjustments for Bing campaigns by increasing the budget by 5% for campaigns that meet specific performance criteria over the past 30 days.
Purpose:
The Python script automates the process of copying and updating Epicor monthly budgets from Google Sheets to a staging area at the start of each month.
Purpose
Python script to pause and re-enable campaigns based on budget allocation.
Purpose
Set dimensions based on campaign name.
Purpose:
The Python script manages advertising campaigns by pausing them when the month-to-date (MTD) spend reaches the Epicor Monthly Budget, ensuring budget compliance.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR, Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance to previous 6 months.
Purpose
Tag Dimensions based on CRV, CPL, CPC, CTR performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose:
The Python script updates the status, target CPA, and daily budget for new launch campaigns based on specified ROAS criteria.
Purpose:
The Python script automates the update of campaign statuses, bid strategies, and target CPA for new launch campaigns based on performance metrics.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose:
The Python script updates the ‘Amazon Portfolio’ column in a DataFrame to match the ‘Portfolio’ column when discrepancies or null values are found.
Purpose:
The Python script updates the status, target cost-per-acquisition (tCPA), bid strategy, and maturity of new launch campaigns based on specified return on ad spend (ROAS) criteria.
Purpose
Python script for media type tagging.
Purpose:
The Python script categorizes media campaigns by tagging them with specific media types and sub-types based on predefined criteria.
Purpose:
The Python script categorizes media campaigns by assigning media types and subtypes based on specific keywords in the campaign data.
Purpose
Python script for tagging media types and subtypes in a dataset.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months
Purpose
Python script to tag campaigns based on the comparison between the publisher cost and the daily budget.
Purpose
Tag Dimensions based on CVR, CPL, CPC, and CTR Performance compared to Preset Benchmarks
Purpose:
The Python script allocates daily budgets for each Epicor Budget Group by considering remaining budgets, weekdays, historical spending, and campaign activity.
Purpose:
The script enforces monthly budget caps for advertising strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose
Python script solves the problem of adjusting the Publisher Target ROAS for Google campaigns based on the daily spend goal and publisher cost.
Purpose
Python script to assign campaign dimension values based on strategy/targeting type and campaign tactic.
Purpose:
The Python script assigns campaign dimension values based on specific patterns found in campaign names.
Purpose
Reduce the daily budget of campaigns by 20% if the GAAP profit from the previous day is less than 0.
Purpose:
The Python script assigns a specific campaign strategy and publisher strategy based on the current date matching the “CPA Date” in the data.
Purpose:
The Python script evaluates advertising campaigns to determine if they meet specific criteria for switching to a new publisher bidding strategy based on minimum ROAS and spend thresholds.
Purpose:
The script adjusts the daily budget of campaigns by increasing it by 20% if the daily spend exceeds 60% of the current daily budget.
Purpose:
The Python script ensures that the SBA Pause Date remains within one month of the current date to allow the tool to unpause it.
Purpose:
The Python script processes marketing data to assign strategies based on performance metrics over specific time periods.
Purpose:
The Python script evaluates the pacing of campaigns against their structured budget allocation targets by analyzing conversion data.
Purpose
Python script for tagging campaigns as “Brand” or “Non Brand” based on the campaign name.
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The Python script updates a DataFrame by copying yesterday’s cost data from one column to another.
Purpose:
The Python script updates a DataFrame by copying yesterday’s publication cost to a specific column for structured budget allocation purposes.
Purpose:
The Python script updates a DataFrame by copying yesterday’s publication cost into a specific column for structured budget allocation purposes.
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to populate the “Campaign Category” column in a DataFrame based on specific rules.
Purpose:
The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
In a Nutshell
The script updates the region information for PPC campaigns based on campaign naming conventions.
Purpose Python script that recommends changes to tROAS (target ROAS) and daily budget for Google Ads campaigns based on the performance of non-brand new customer ROAS over the last 30...
Purpose: The Python script ensures that the traffic dimension is consistently aligned across each bucket by setting all campaigns in a bucket to the maximum traffic value when one campaign...
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to add dimensions tag based on campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose
Python script to add dimensions tag based on campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose:
The script adjusts the target CPA and daily budget of Google campaigns based on recent ROAS and spending data.
Purpose:
The script identifies and pauses mature advertising campaigns with low Return on Ad Spend (ROAS) over the past 14 days.
Purpose:
The script assigns market identifiers to campaigns based on specific patterns in campaign names.
Purpose
The script adjusts the target cost-per-action (tCPA) for campaigns based on their current cost per conversion, increasing it if the cost is below a specified threshold.
Purpose:
The Python script categorizes marketing campaigns into “Brand” or “Non-Brand” based on specific naming patterns.
Purpose:
The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘Mature’ based on their ROAS over the previous 14 days.
Purpose:
The Python script categorizes ExplorAds and Yahoo DSP campaigns into maturity labels based on their spending thresholds over the past year.
Purpose:
The Python script automates the assignment of “Brand vs NonBrand” dimensions to campaigns based on their names.
Purpose:
The Python script automates the process of switching campaign publisher bidding strategies to Target CPA based on minimum spend and ROAS criteria.
Purpose:
The Python script automates the process of pausing new advertising campaigns with low Return on Advertising Spend (ROAS) based on predefined criteria.
Purpose
The script increases the daily budget for campaigns with an impression share greater than a specified percentage over the last specified number of days.
Purpose: The Python script adjusts the target CPA and daily budget of Google campaigns labeled as ‘New Launch’ through ‘New - Round 5’ based on their ROAS over the past...
Purpose:
The Python script tags campaigns as ‘Brand’ or ‘Non-Brand’ based on the presence of the word ‘Brand’ in the campaign name.
Purpose:
The Python script categorizes campaigns into ‘Brand’ or ‘Non-Brand’ based on their names and outputs the results.
Purpose:
The Python script assigns a specific label to campaigns based on certain conditions in a dataset.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The script parses campaign names to extract and assign a tag based on a specific naming convention.
Purpose:
The Python script adjusts SBA targets by applying a target factor to raw targets.
Purpose
Reset Campaign Daily Budget by either 50% or pre-defined amount at start of each month.
Purpose:
The Python script enforces monthly budget caps for strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose:
The Python script identifies and tags campaigns with significantly lower Return on Advertising Spend (ROAS) compared to their peers within the same account.
Purpose:
The Python script reassigns advertising strategies to campaigns based on their Month-to-Date conversion levels.
Purpose: The Python script adjusts campaign budgets by increasing them by 5% if the Cost Per Acquisition (CPA) performance is 10% better than the average of peers within the same...
Purpose: The Python script adjusts the budget of non-brand advertising campaigns by 5% if their cost-per-acquisition (CPA) performance is 10% better than the average of their peers within the same...
Purpose
Pause campaigns with no active groups.
Category Featured
Purpose:
The Python script adjusts revenue and conversion data at the keyword level based on latency factors to provide more accurate estimates.
Purpose:
The Python script analyzes and summarizes the performance of marketing strategies by comparing actual results against targets, categorizing them based on management levels, and providing insights for optimization.
Purpose
The Python script ingests media plan spend targets from a Google Sheets document and maps them to strategies for the current month.
Purpose
Python script that takes the unspent Strategy Spend Target from the previous month and adds it to the current Spend Target.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script generates a performance anomaly report for pay-per-click marketing campaigns.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets, specifically supporting Google Smart Bidding strategies.
Purpose:
The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose:
The Python script identifies anomalies in campaign performance metrics for hotels by using day-of-week forecasts and calculating deviations based on user-defined thresholds.
Purpose:
The script enforces monthly budget caps for advertising strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose:
The Python script processes keyword data to manage and optimize advertising campaigns by pausing certain keywords based on performance metrics.
Purpose:
The script parses campaign names to extract and assign a tag based on a specific naming convention.
Purpose:
The Python script enforces monthly budget caps for strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Purpose: The script automates the creation of suggested keywords from a keyword expansion report, focusing on long keywords with six or more tokens and setting them with specific attributes for...
Purpose:
The Python script reassigns advertising strategies to campaigns based on their Month-to-Date conversion levels.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose: The Python script adjusts campaign budgets by increasing them by 5% if the Cost Per Acquisition (CPA) performance is 10% better than the average of peers within the same...
Category Action Type - Bulk Upload
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
Purpose:
The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
Purpose:
The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
Purpose:
The Python script dynamically allocates recommended daily budgets to campaigns based on input data.
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The script pauses ad groups with fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The Python script pauses ad groups with over 100 clicks that have not generated any Prime Starts/Conversions in the past 30 days, ensuring they have been active for at...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation for digital marketing campaigns, ensuring they meet specific goals and constraints.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The Python script automates the process of updating daily budget allocations for advertising campaigns based on recommended values.
Purpose:
The script compares daily budget allocations to actual spending to assess pacing and budget status for advertising campaigns.
Purpose:
The Python script automates the merging and filtering of data from multiple sources to facilitate structured budget allocation for CCT incentives.
Purpose:
The script extracts the country code from a group name by identifying the segment before the first hyphen.
Purpose:
The script extracts country codes and friendly names from campaign names in a dataset.
Purpose:
The Python script extracts the ‘REF Marker’ from the ‘Landing Page’ column and assigns it to the ‘REF Marker’ dimension in a structured data format.
Purpose:
The script extracts and processes Marketo IDs from campaign names in a dataset.
Purpose:
The Python script processes campaign data to extract and map program codes to their full names, creating a structured output for further analysis.
Purpose:
The script automatically labels campaign dimensions based on the campaign naming convention and campaign type.
Purpose:
The Python script extracts the Line of Business (LOB) tag from campaign names by identifying the value between the first and second underscores.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script categorizes pacing percentages into descriptive tags such as ‘On Target’, ‘Under Pacing’, ‘Over Pacing’, etc., based on predefined ranges.
Purpose:
The script transfers Microsoft purchase conversion data into a new column labeled “Last365Days Conversions” within a dataset.
Purpose:
The Python script automates the pausing and re-enabling of advertising campaigns based on their monthly budget targets and current spending.
Purpose: The Python script manages campaign budgets by automatically pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget and re-enabling them when the spend falls below the budget....
Purpose
The Python script automates the process of allocating and updating daily budgets for advertising campaigns based on recommended values from a data source.
Purpose:
The Python script dynamically allocates and updates daily budgets for advertising campaigns based on recommended values.
Purpose:
The Python script extracts and tags the campaign strategy from the campaign name based on specific delimiters.
Purpose:
The script extracts and tags the numeric value before the first dash in a campaign name, removing any parentheses.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script assigns a strategy to campaigns that are currently marked as ‘Unassigned’ based on a specific naming pattern.
Purpose:
The Python script adjusts daily budgets for advertising campaigns based on pacing cycles and specific criteria to optimize spending.
Purpose
The script updates monthly budgets for strategies by matching them with concatenated values from a Google Sheet.
Purpose:
The Python script automatically tags manufacturer names based on keywords found in campaign names within a dataset.
Purpose: The Python script calculates the pacing of advertising strategies at the campaign level by comparing month-to-date spending against expected spending based on the total budget and elapsed days in...
Purpose:
The Python script calculates the adjusted daily budget for strategies at the campaign level based on remaining budget and days left in the month.
Purpose:
The Python script sets benchmarks for individual campaigns and strategies by analyzing performance metrics over specified time periods.
Purpose:
The Python script tags county codes to campaigns based on their names in a DataFrame.
Purpose:
The Python script transfers values from the “Portfolio” column to the “Amazon Portfolio” column in a dataset.
Purpose:
The script automates the process of tagging groups with fund type dimensions by matching data from a primary source with a reference Google Sheet.
Purpose:
The Python script tags groups with a FUND dimension based on abbreviations found in group names.
Purpose:
The Python script calculates and manages pacing and budget allocation for digital advertising campaigns, ensuring they meet their goals efficiently.
Purpose:
The Python script calculates and manages campaign pacing and budget allocation based on various metrics and goals for digital marketing campaigns.
Purpose:
The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
Purpose:
The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
Purpose
Automatically tags the “Product” dimension based on the product detail page URL of an ad.
Purpose:
The Python script automatically tags marketing campaigns with a service dimension based on the campaign name.
Purpose:
The Python script tags product types based on campaign names in a DataFrame.
Purpose:
The script identifies and tags US states mentioned in the “Campaign” column of a DataFrame.
Purpose:
The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria within a dataset.
Purpose:
The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
Purpose:
The Python script sets a Target CPA Cap of $1000 for all active strategies or campaigns where the current CPA exceeds this limit.
Purpose:
The Python script clears existing dimension values to ensure only the top 20 keywords are labeled for the next day’s dimension script.
Purpose:
The Python script identifies and labels the top 10 performing keywords based on cost per conversion from a sorted report.
Purpose:
The script identifies and tags the top-performing keywords in a Google Ads report based on cost per conversion.
Purpose:
The script assigns dimension labels to campaigns based on their naming conventions and campaign types.
Purpose:
Automates the process of updating a remarketing dimension in a dataset based on specific campaign name values.
Purpose:
Automates the process of populating the brand dimension in a dataset based on specific rules applied to campaign name and type values.
Purpose:
Automates the categorization of campaigns by analyzing campaign names and assigning them to predefined categories.
Purpose:
Automates the process of populating device and match type dimensions in a dataset based on campaign name values.
Purpose:
Automates the process of populating subregion dimensions in a dataset based on campaign name values.
Purpose:
The Python script categorizes PPC scores into letter grades ranging from A to D based on predefined score ranges.
Purpose:
Automates the process of updating UTM group dimensions based on ad group names by replacing spaces with plus signs.
Purpose:
Automates the population of utmcampaign and utmmedium dimensions based on campaign name and type.
Purpose
The Python script processes keyword data to generate a structured keyword template based on specific group terms.
Purpose:
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend reaches the monthly budget specified in the strategy.
Purpose:
This Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on cost per conversion over the last 60 days for each school program.
Purpose:
The Python script processes a DataFrame to extract and categorize information about campaigns, including studio names, feed categories, and language targets.
Purpose:
The Python script updates benchmark dimensions in Marin by copying data from a staging Google Sheet, matching the ‘Abbreviation’ column with the ‘Strategy’ column.
Purpose:
The Python script processes a DataFrame to extract and replace search phrases from keywords based on a given title, creating a new column with the modified keyword.
Purpose:
The Python script extracts a title from a “Group” column using a regex pattern and updates the “Title” column accordingly.
Purpose:
The Python script calculates and tags campaigns with strategy-level benchmark scores for metrics such as MTD Gross Lead, CPL, CPL Trend, and Interview Rate.
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose:
The Python script filters and processes campaign data to identify and update daily budget alerts for campaigns marked as “Checked.”
Purpose: The Python script tags Meta Ads campaigns at the ad level based on performance metrics such as eCPM and CTR, categorizing them as “winning” or “losing” according to predefined...
Purpose:
The Python script tags Meta Ad Groups based on their performance metrics, categorizing them as “winning” or “losing” according to predefined business rules.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The script extracts and assigns a country code from a group name into a designated column based on specific parsing rules.
Purpose:
The script extracts and categorizes campaign types and game names from campaign names in a dataset.
Purpose:
The Python script automates the tagging of media types and sub-types for advertising campaigns based on specific account and publisher name criteria.
Purpose:
The Python script tags Meta campaign dimensions based on performance metrics to determine if they are “winning” or “losing.”
Purpose:
The Python script identifies and recommends pausing keywords in advertising campaigns that are at least 30 days old, have zero conversions, and a quality score below 5.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
Matches the SBA Strategy Name and Targets to the Dynamic Allocation ones.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose:
The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a dataset, ensuring it is reset to an empty state.
Purpose:
The Python script is designed to clear the ‘AUTOMATION - Outlier’ column in a data set, effectively resetting its values.
Purpose:
The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose:
The Python script is designed to clear and reset the ‘AUTOMATION - Outlier’ column in a data table to prepare it for further processing.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is abnormally high based on a 30-day lookback period, excluding the most...
Purpose:
The script identifies and tags the top 10 keywords as “Top Performer” based on conversion count and cost per conversion over the last 60 days.
Purpose:
The Python script tags campaigns based on their performance metrics compared to predefined benchmarks, assigning tags like “Over Target,” “Under Target,” and “On Target.”
Purpose
The script extracts the country code from a group name by identifying the segment before the first hyphen and assigns it to a ‘Country Code’ dimension.
Purpose
The script automates the extraction and tagging of the “Country Code” dimension from campaign names for Carburant’s Square Enix, excluding Meta publishers.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion metrics and cost efficiency over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion and cost per conversion metrics over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 performing keywords based on conversion and cost per conversion over the last 60 days.
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than normal, using a 30-day lookback period excluding the...
Purpose:
The Python script extracts and assigns a campaign type from campaign names based on a specific tag format.
Purpose:
The Python script extracts project numbers from campaign names by identifying tags that appear after a specified delimiter and assigns them to a designated dimension.
Purpose:
The script updates the ‘Campaign CPA This Quarter’ column with the current quarter’s CPA values for each campaign.
Purpose:
The Python script updates strategy spend targets by copying program budgets from Google Sheets to a local data structure.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose
Python script to copy values from the ‘Strategy’ and ‘Strategy Target’ columns to the ‘SBA Strategy’ and ‘SBA Campaign Budget’ columns, respectively.
Purpose: The Python script identifies and tags AdGroups with abnormally high Cost Per Acquisition (CPA) performance within a campaign using a 30-day lookback period, excluding the most recent 3 days....
Purpose: The Python script identifies and tags AdGroups within a campaign where the Cost Per Acquisition (CPA) performance is significantly higher than expected, using a 30-day lookback period excluding the...
Purpose:
The Python script automates the process of tagging campaigns with the appropriate program manager based on data from Google Sheets.
Purpose:
The Python script processes campaign data to identify and tag audience and segment information based on predefined keywords.
Purpose:
The Python script extracts and categorizes geographical, segment, targeting, and platform information from campaign names in a dataset.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
Purpose:
The script extracts keyword match types from campaign names and updates a data frame accordingly.
Purpose:
The Python script identifies and tags the intent of marketing campaigns based on specific keywords found in campaign names.
Purpose:
The Python script processes campaign data to extract and assign topics based on a structured naming convention.
Purpose
The Python script manages campaign budgets by pausing campaigns when the month-to-date (MTD) spend approaches or exceeds the monthly budget set in a strategy.
Purpose:
The Python script manages the automatic pausing and re-enabling of advertising campaigns based on monthly budget targets defined in strategies.
Purpose
Python script to pause and resume campaigns based on monthly budget spend.
Purpose:
The Python script extracts and tags the “F-YY-Brand” from campaign names in a dataset, ensuring structured budget allocation.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, spend potential, and remaining budget.
Purpose:
The script extracts and categorizes tags from non-brand campaign names in a dataset.
Purpose:
The Python script automates the process of calculating and adjusting daily budgets for marketing campaigns based on structured budget allocation (SBA) strategies.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
Purpose:
The script identifies campaigns with a significant discrepancy between the assigned “Two Year Cost (Publisher)” and the actual publisher cost over the last two years.
Purpose:
The Python script alerts the Program Manager when the percentage difference in a dataset is 15% or more, either positively or negatively.
Purpose
Python script to pause ad groups in select model-based new vehicle campaigns if there are 3 or fewer vehicles in stock.
Purpose:
Automatically tags marketing campaigns as either Brand or NonBrand based on their names.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for Category.
Purpose
Python script to parse campaign names and add campaign-level Marin Dimensions Tag for campaign type.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The script automates the assignment of bidding strategies to campaigns based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automatically assigns a campaign to a specific bidding strategy based on the campaign’s age.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose:
The Python script automates the assignment of advertising campaigns to specific bidding strategies based on their creation date.
Purpose
Python script that allocates budgets to campaigns based on various factors such as remaining budget, weekdays in the month, historical spend, and minimum daily budget.
Purpose:
The script updates the “Keyword Cost/Conv Performance” dimension for keywords whose cost per conversion is 30% greater than their campaign’s cost per conversion.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and remaining weekdays in the month.
Purpose:
The Python script updates the “Campaign 30 Day Cost per Conversion” dimension daily to support keyword-level anomaly detection for cost per conversion.
Purpose
Pause Poor performing Keywords with 0 Conv. and QS <5
Purpose:
The Python script identifies and tags campaigns where the previous day’s spending is at least 90% of the daily budget and certain conditions are met.
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies and tags campaigns where the publisher cost for the prior day is at least 90% of the daily budget, indicating a potential budget cap situation....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher’s cost for the previous day is at least 90% of the daily budget and flags them with a “Budget Capped” alert....
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the publisher cost for the prior day is at least 90% of the daily budget and flags them as “Budget Capped.”
Purpose: The Python script identifies campaigns where the publisher cost for the previous day is at least 90% of the daily budget and flags them as “Budget Capped” if certain...
Purpose:
The Python script identifies campaigns where the previous day’s spending was at least 90% of the daily budget and flags them if certain conditions are met.
Purpose: The Python script identifies campaigns where the previous day’s spending is at least 90% of the daily budget and flags them as “Budget Capped” if certain conditions are met....
Purpose
Parse Campaign Name and add Campaign-level Marin Dimensions Tag for Placement.
Purpose:
The Python script identifies keywords with duplicate MKWID values and prepares them for reupload with blank custom parameters.
Purpose:
The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by considering historical spend, remaining budget, and potential spend.
Purpose
Auto Tag Campaign with Tipo de Campanha Dimension
Purpose
Automatically tags campaigns with ‘Brand’ or ‘NonBrand’ based on specific keywords in the campaign name.
Purpose
Auto Tag the funnel stage of campaigns based on the campaign name.
Purpose:
Calculates the difference between SBA allocation and the percentage of total publication cost.
Purpose: The Python script calculates the total publication cost for each ‘SBA Strategy’ and ‘Campaign’ group and determines the percentage of ‘Pub. Cost $’ for each row relative to the...
Purpose: The Python script optimizes campaign budget allocation to minimize lost impression share due to budget constraints by calculating recommended daily budgets based on historical spend, remaining budget, and pacing...
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose:
The Python script extracts specific information from campaign names and organizes it into a structured format for further analysis.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
Remove the dollar sign ($) from the SBA Campaign Budget column in a given input dataframe.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose
Python script to filter and manipulate data from a primary data source based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing and traffic conditions.
Purpose This Python script calculates various metrics and values for a campaign, such as total impressions, total clicks, total views, pacing cycle start and end dates, daily targets, expected spend...
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific conditions.
Purpose:
The Python script calculates and manages pacing metrics for digital advertising campaigns to ensure they meet their budget and performance goals.
Purpose
Python script to filter and process campaign data based on specific criteria.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose This Python script solves the problem of calculating various metrics and values for a campaign, such as total pub cost, total impressions, total clicks, total views, pacing cycle start...
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and traffic conditions.
Purpose:
The Python script processes campaign data to adjust daily budgets based on pacing cycles and specific business rules.
Purpose:
The script calculates and stores the average cost-per-click (CPC) for the last 28 days in a specified dimension called “Test.”
Purpose:
The Python script automates the pausing and resuming of advertising campaigns based on their monthly budget and current spending, using dimension tags for structured budget allocation.
Purpose
The Python script automatically pauses or resumes marketing campaigns based on their month-to-date (MTD) spending relative to a predefined budget cap.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation (SBA) processes.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The script automatically tags campaigns as “Brand” or “Non-Brand” based on the campaign name, specifically tagging as “Non-Brand” if the name starts with ‘EEE’.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script automates the process of tagging campaigns with combined school and program dimensions and assigns an SBA strategy based on these tags.
Purpose
Python script that combines the ‘School’ and ‘Program’ columns into a new column called ‘School_Program’ and assigns the created tag to the ‘School_Program’ column.
Purpose:
The script parses campaign names to automatically tag them with a program identifier based on a specific naming convention.
Purpose:
The Python script parses campaign names to automatically tag them with a school dimension based on the text before the first underscore.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to enhance structured budget allocation.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose:
The Python script is designed to optimize daily budget allocation for Search SBA strategies by minimizing lost impression share due to budget constraints.
Purpose:
The script assigns Meta ABO Budget values at the group level for active Meta Ad sets, removing any previously assigned values at the campaign level.
Purpose:
The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose:
The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose:
The Python script processes and updates group statuses based on keyword and studio conditions to manage campaign groups effectively.
Purpose
SBA Campaign Budget Pacing - Minimize Lost IS (Budget)
Purpose:
The Python script assigns geographic values to the ‘Geo’ dimension at the campaign level based on specific keywords found in campaign names.
Purpose:
The script extracts pacing dates and goals from campaign names in a dataset to populate missing information.
Purpose
Pace Daily Budget for each Strategy
Purpose:
The Python script automates the tagging of campaigns as either “Brand” or “Generic” based on specific keywords in account and campaign names.
Purpose
Python script that looks for duplicate campaigns created by Dynamic Campaigns and sets the status to “Deleted” for any older campaigns.
Purpose: The Python script assigns corrected budget values at the campaign level to a dimension called “Meta ABO Budget” and labels campaigns as using ABO Budgets by setting the “Budget...
Purpose
The Python script optimizes budget allocation for marketing campaigns to minimize lost impression share due to budget constraints.
Purpose:
The Python script extracts and updates start and end dates from campaign names in a dataset, ensuring they are in a standardized format.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script extracts and updates pacing start and end dates from campaign names in a dataset.
Purpose:
The Python script updates a dataset to set the “Historical Quality Score - 1st of the month” dimension with the current quality score value for each keyword.
Purpose
Tag Brand vs Non Brand dimension automatically
Purpose:
The Python script assigns dimension values to campaigns based on their names, categorizing them as “Brand,” “Local,” or “Emergency.”
Purpose
Python script to tag ad groups if their CPA performance is abnormally high within a campaign.
Purpose
The Python script calculates the “Set Rate” for campaigns by aggregating six months of data, excluding the most recent 30 days, to account for latency.
Purpose:
The Python script automates budget adjustments for Bing campaigns by increasing the budget by 5% for campaigns that meet specific performance criteria over the past 30 days.
Purpose:
The Python script automates the process of copying and updating Epicor monthly budgets from Google Sheets to a staging area at the start of each month.
Purpose:
The Python script identifies and tags AdGroups with abnormally low Cost/Conversion performance within a campaign over a specified lookback period.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly assigned based on specific conditions.
Purpose:
The Python script merges data from two sources, processes URLs, and prepares a structured output for further use.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly formatted based on specific conditions.
Purpose:
The Python script processes and merges data from two sources to prepare a structured dataset for email marketing campaigns.
Purpose:
The Python script processes marketing data to determine and populate the “NTB Uplift” dimension based on specific business conditions.
Purpose
Set dimensions based on campaign name.
Purpose:
The Python script manages advertising campaigns by pausing them when the month-to-date (MTD) spend reaches the Epicor Monthly Budget, ensuring budget compliance.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR, Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance to previous 6 months.
Purpose
Tag Dimensions based on CRV, CPL, CPC, CTR performance compared to previous 6 months.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months.
Purpose:
The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
Purpose
Python script to tag campaigns based on their performance metrics compared to benchmarks.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize advertising campaigns.
Purpose:
The Python script updates the ‘Amazon Portfolio’ column in a DataFrame to match the ‘Portfolio’ column when discrepancies or null values are found.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for email import, ensuring URLs are correctly formatted and assigned.
Purpose
Python script for media type tagging.
Purpose:
The Python script categorizes media campaigns by tagging them with specific media types and sub-types based on predefined criteria.
Purpose:
The Python script categorizes media campaigns by assigning media types and subtypes based on specific keywords in the campaign data.
Purpose
Python script for tagging media types and subtypes in a dataset.
Purpose:
The Python script categorizes media types and sub-types based on specific keywords found in account, campaign, and group data.
Purpose:
The Python script categorizes media types and sub-types based on specific account and group criteria in a dataset.
Purpose:
The Python script categorizes media types and sub-types based on specific keywords found in account and campaign data.
Purpose:
The Python script automates the tagging of media types and subtypes based on specific account and campaign criteria in a dataset.
Purpose
Tag Dimensions based on CVR, CPL, CPC, CTR Performance compared to previous 6 months
Purpose
Python script to tag campaigns based on the comparison between the publisher cost and the daily budget.
Purpose
Tag Dimensions based on CVR, CPL, CPC, and CTR Performance compared to Preset Benchmarks
Purpose:
The Python script is designed to clear the ‘Conversion Influencers’ dimension values in a dataset.
Purpose:
The Python script identifies and labels the top 10 keywords based on cost per conversion over the last 60 days, requiring at least one conversion to be considered.
Purpose:
The Python script allocates daily budgets for each Epicor Budget Group by considering remaining budgets, weekdays, historical spending, and campaign activity.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
Purpose:
The Python script processes input data to generate an output with specific default values for certain columns related to advertising campaigns.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to set specific parameters for product substitution in a marketing campaign.
Purpose:
The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
Purpose:
The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
Purpose:
The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.
Purpose:
The script updates custom parameters for keywords with specific tags in the landing page result column.
Purpose:
The script updates custom parameters for keywords with specific tags in the landing page result column.
Purpose
Python script to assign campaign dimension values based on strategy/targeting type and campaign tactic.
Purpose:
The Python script adjusts search bids for advertising campaigns based on specific criteria and conditions to optimize performance.
Purpose:
The Python script adjusts the “FullFunnel” strategy for marketing campaigns based on specific ratio criteria.
Purpose:
The Python script ensures that the SBA Pause Date remains within one month of the current date to allow the tool to unpause it.
Purpose:
The Python script evaluates the pacing of campaigns against their structured budget allocation targets by analyzing conversion data.
Purpose
Python script for tagging campaigns as “Brand” or “Non Brand” based on the campaign name.
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose:
The Python script updates a DataFrame by copying yesterday’s cost data from one column to another.
Purpose:
The Python script updates a DataFrame by copying yesterday’s publication cost to a specific column for structured budget allocation purposes.
Purpose:
The Python script updates a DataFrame by copying yesterday’s publication cost into a specific column for structured budget allocation purposes.
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to populate the “Campaign Category” column in a DataFrame based on specific rules.
Purpose:
The script transfers yesterday’s cost data from a report to a bulk data format for further processing.
In a Nutshell
The script updates the region information for PPC campaigns based on campaign naming conventions.
In a Nutshell
The script processes PPC campaign data to update event names based on specific patterns in group names.
Purpose Python script that recommends changes to tROAS (target ROAS) and daily budget for Google Ads campaigns based on the performance of non-brand new customer ROAS over the last 30...
Purpose: The Python script ensures that the traffic dimension is consistently aligned across each bucket by setting all campaigns in a bucket to the maximum traffic value when one campaign...
Purpose:
The Python script transfers yesterday’s cost data from a report to a bulk data format for further processing.
Purpose
Python script to add dimensions tag based on campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose
Python script to add a dimensions tag based on the campaign name.
Purpose:
The script assigns market identifiers to campaigns based on specific patterns in campaign names.
Purpose:
The script checks if the “IB Last Updated” date is two or more days old and flags it for alert if certain conditions are met.
Purpose:
The Python script categorizes marketing campaigns into “Brand” or “Non-Brand” based on specific naming patterns.
Purpose:
The Python script automates the assignment of “Brand vs NonBrand” dimensions to campaigns based on their names.
Purpose:
The Python script tags campaigns as ‘Brand’ or ‘Non-Brand’ based on the presence of the word ‘Brand’ in the campaign name.
Purpose
Auto Pause After Event Date
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
Purpose:
The script determines auction boost amounts for groups in specific campaigns based on various criteria, including pageviews, PUP scores, and shoot prices.
Purpose:
The Python script adjusts SBA targets by applying a target factor to raw targets.
Purpose
Reset Campaign Daily Budget by either 50% or pre-defined amount at start of each month.
Purpose: The Python script dynamically adjusts bid values for ad groups based on historical and target Return on Advertising Spend (ROAS) to optimize advertising strategies across clients in the Dutch...
Purpose
Clear Daily Winner and Overspend labels daily
Purpose
Tag AdGroup Dimensions per ROAS/CPA Performance
Purpose:
The Python script identifies and tags AdGroups with abnormally low ROAS performance within a campaign over a specified lookback period.
Category Item Changed - Keyword
Purpose:
The script pauses keywords with 0 conversions and 60+ clicks in the last 60 days, ensuring they have been active for at least 60 days.
Purpose:
The Python script extracts the ‘REF Marker’ from the ‘Landing Page’ column and assigns it to the ‘REF Marker’ dimension in a structured data format.
Purpose:
The Python script processes marketing data to determine and populate the ‘NTB Uplift’ metric based on specific conditions related to revenue and new customer acquisition.
Purpose:
The Python script pauses keywords with more than 100 clicks and a cost per conversion above €2 for the last 7 days.
Purpose:
The Python script pauses keywords in a report that have between 10 and 100 clicks and a cost per conversion greater than €2.80 over the last 7 days.
Purpose:
The Python script pauses keywords with more than 10 clicks and a conversion rate below 10%.
Purpose:
The Python script identifies and recommends pausing keywords that are at least 30 days old, have zero conversions, and a quality score below 5.
Purpose:
The script qualifies suggested keywords based on conversion rates, CPA thresholds, and token count limits for effective ad targeting.
Purpose:
The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
Purpose:
The script tags the “Current Organic Average Position” dimension with the previous day’s Organic Average Position from Google Search Console data.
Purpose:
The Python script clears existing dimension values to ensure only the top 20 keywords are labeled for the next day’s dimension script.
Purpose:
The Python script identifies and labels the top 10 performing keywords based on cost per conversion from a sorted report.
Purpose:
The script identifies and tags the top-performing keywords in a Google Ads report based on cost per conversion.
Purpose
The Python script processes keyword data to generate a structured keyword template based on specific group terms.
Purpose:
This Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on cost per conversion over the last 60 days for each school program.
Purpose:
The Python script processes a DataFrame to extract and replace search phrases from keywords based on a given title, creating a new column with the modified keyword.
Purpose:
The script identifies conflicting keywords between current and negative keyword lists in an account.
Purpose:
The Python script identifies and recommends pausing keywords in advertising campaigns that are at least 30 days old, have zero conversions, and a quality score below 5.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The Python script identifies and tags the 10 most underperforming keywords within both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the 10 most underperforming keywords in both “Brand” and “NonBrand” categories based on conversion metrics.
Purpose:
The script identifies and tags the top 10 keywords as “Top Performer” based on conversion count and cost per conversion over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion metrics and cost efficiency over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 keywords as “Top Performer” based on conversion and cost per conversion metrics over the last 60 days.
Purpose:
The Python script identifies and tags the top 10 performing keywords based on conversion and cost per conversion over the last 60 days.
Purpose
Automating Dimension Tagging with the landing page in the dimension “Landing Page Dim” and the keyword and match type combination in the dimension “Keyword MatchType Dim”.
Purpose:
The script updates the “Keyword Cost/Conv Performance” dimension for keywords whose cost per conversion is 30% greater than their campaign’s cost per conversion.
Purpose
Pause Poor performing Keywords with 0 Conv. and QS <5
Purpose:
The Python script identifies keywords with duplicate MKWID values and prepares them for reupload with blank custom parameters.
Purpose:
The Python script generates negative keywords for single keyword campaigns by cross-negating keywords within each account.
Purpose:
The Python script updates a dataset to set the “Historical Quality Score - 1st of the month” dimension with the current quality score value for each keyword.
Purpose
Python script to auto-push a subset of suggested keywords from a keyword recommendations grid.
Purpose:
The Python script processes marketing data to determine and populate the “NTB Uplift” dimension based on specific business conditions.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation in advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize advertising campaigns.
Purpose:
The Python script adjusts keyword headroom based on historical performance data to optimize budget allocation.
Purpose:
The Python script is designed to clear the ‘Conversion Influencers’ dimension values in a dataset.
Purpose:
The Python script identifies and labels the top 10 keywords based on cost per conversion over the last 60 days, requiring at least one conversion to be considered.
Purpose
Python script for negative keyword expansion.
Purpose:
The Python script adjusts search bid values and bid override statuses for keywords in advertising campaigns based on specific performance criteria.
Purpose:
The Python script adjusts search bids for advertising campaigns based on specific criteria and conditions to optimize performance.
Purpose:
The Python script adjusts the “FullFunnel” strategy for marketing campaigns based on specific ratio criteria.
Purpose:
The Python script processes keyword data to manage and optimize advertising campaigns by pausing certain keywords based on performance metrics.
Purpose:
The Python script automates the process of pausing keywords and labeling them with the ‘AutoPause’ dimension based on specific criteria related to creation date, accumulated clicks, and spend.
Purpose: The script automates the creation of suggested keywords from a keyword expansion report, focusing on long keywords with six or more tokens and setting them with specific attributes for...
Category Reference Datasource - Google Sheets
Purpose:
The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
Purpose:
The Python script automates the merging and filtering of data from multiple sources to facilitate structured budget allocation for CCT incentives.
Purpose
The script processes and merges campaign budget data from a primary data source and Google Sheets to update daily budgets for campaigns.
Purpose:
The script automates the process of setting daily budgets for campaigns by merging data from a primary data source with a Google Sheets reference.
Purpose:
The Python script processes offline booking data by copying it from a primary data source to an output data frame, allowing for custom output columns.
Purpose:
The Python script processes and merges campaign budget data from a primary data source and a Google Sheets reference to prepare a structured budget allocation for campaigns.
Purpose:
The Python script processes and exports account data from a primary data source without modifications.
Purpose
The script updates monthly budgets for strategies by matching them with concatenated values from a Google Sheet.
Purpose
The script updates monthly budget targets for strategies by matching them with concatenated values from a Google Sheet.
Purpose:
The script automates the process of tagging groups with fund type dimensions by matching data from a primary source with a reference Google Sheet.
Purpose:
The Python script tags groups with a FUND dimension based on abbreviations found in group names.
Purpose:
The Python script synchronizes campaign budget data from a primary data source with updates from a Google Sheets reference, ensuring daily budget allocations are current.
Purpose:
The script processes and merges data from two sources to produce a structured output for wishlist ingestion.
Purpose:
The Python script automates the process of enabling a campaign override flag when adjusted recommendations exceed predefined caps set in Google Sheets.
Purpose:
The Python script updates benchmark dimensions in Marin by copying data from a staging Google Sheet, matching the ‘Abbreviation’ column with the ‘Strategy’ column.
Purpose
The Python script ingests media plan spend targets from a Google Sheets document and maps them to strategies for the current month.
Purpose
Lookup new month’s spend target and update via strategy bulk file
Purpose:
The Python script updates strategy spend targets by copying program budgets from Google Sheets to a local data structure.
Purpose:
The Python script automates the process of tagging campaigns with the appropriate program manager based on data from Google Sheets.
Purpose:
The Python script automates the process of updating strategy spend targets by copying monthly budget data from customer-maintained Google Sheets and matching it with strategies in Marin.
Purpose:
The Python script automates the process of copying and updating monthly budget allocations from Google Sheets to a structured budget allocation system by matching campaign strategies.
Purpose:
The Python script automates the process of copying and updating Epicor monthly budgets from Google Sheets to a staging area at the start of each month.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly assigned based on specific conditions.
Purpose:
The Python script merges data from two sources, processes URLs, and prepares a structured output for further use.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly formatted based on specific conditions.
Purpose:
The Python script processes and merges data from two sources to prepare a structured dataset for email marketing campaigns.
Purpose:
The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
Purpose
This Python script is used to merge data from a primary data source and a reference data source, and then generate an output dataframe.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for email import, ensuring URLs are correctly formatted and assigned.
Purpose:
The Python script enforces monthly budget caps for strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Category Item Changed - Strategy
Purpose
The script updates monthly budgets for strategies by matching them with concatenated values from a Google Sheet.
Purpose
The script updates monthly budget targets for strategies by matching them with concatenated values from a Google Sheet.
Purpose:
The Python script calculates the adjusted daily budget for various strategies based on remaining budget and days in the month.
Purpose
The Python script ingests media plan spend targets from a Google Sheets document and maps them to strategies for the current month.
Purpose
Lookup new month’s spend target and update via strategy bulk file
Purpose
Python script that takes the unspent Strategy Spend Target from the previous month and adds it to the current Spend Target.
Purpose:
The Python script updates strategy spend targets by copying program budgets from Google Sheets to a local data structure.
Purpose:
The Python script automates the process of updating strategy spend targets by copying monthly budget data from customer-maintained Google Sheets and matching it with strategies in Marin.
Purpose
Pushes new Strategy Targets at start of month
Category Reference Datasource - FTP/Email Feed
Purpose:
The script enforces monthly budget caps for advertising strategies and campaigns by pausing those that exceed their allocated budgets, using data from Google Sheets.
Category Item Changed - Ad
Purpose:
The Python script automates the pausing and resuming of webinar ads based on their month-to-date (MTD) spending relative to a predefined monthly budget.
Purpose:
The Python script automates the pausing and reactivation of webinar creatives based on their cost, ensuring efficient budget management.
Purpose:
The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
Purpose:
The Python script automates the merging and filtering of data from multiple sources to facilitate structured budget allocation for CCT incentives.
Purpose
Automatically tags the “Product” dimension based on the product detail page URL of an ad.
Purpose: The Python script tags Meta Ads campaigns at the ad level based on performance metrics such as eCPM and CTR, categorizing them as “winning” or “losing” according to predefined...
Purpose:
The script pauses advertisements if they have zero conversions after spending $100.
Purpose
Pauses ads that have a CPA of $150+ over the previous 7 days
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly assigned based on specific conditions.
Purpose:
The Python script merges data from two sources, processes URLs, and prepares a structured output for further use.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for offline import, ensuring URLs are correctly formatted based on specific conditions.
Purpose:
The Python script processes and merges data from two sources to prepare a structured dataset for email marketing campaigns.
Purpose:
The Python script merges and processes data from two sources to generate a structured dataset for advertising campaigns.
Purpose:
The Python script processes and merges data from two sources to generate a structured dataset for email import, ensuring URLs are correctly formatted and assigned.
Category Action Type - Email Report
Purpose:
The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds and generating a report for analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies outliers in campaign metrics and calculates anomalies using adjustable thresholds to generate a weekly report.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in monthly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes and summarizes the performance of marketing strategies by comparing actual results against targets, categorizing them based on management levels, and providing insights for optimization.
Purpose
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies duplicate keywords in advertising campaigns and recommends which ones to pause based on performance metrics.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies weekly anomalies in campaign performance metrics using configurable thresholds and generates a summary report.
Purpose: The Python script identifies weekly anomalies in campaign performance metrics by analyzing outliers using configurable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a specified...
Purpose:
The Python script calculates predictive revenue values for campaigns using gross lead data and program-level revenue and conversion rates.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies outliers in weekly campaign performance metrics using adjustable thresholds and generates a report accommodating conversion lag.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose: The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a configurable lookback...
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose
The script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies outliers in weekly campaign metrics using adjustable thresholds for anomaly detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script generates a weekly report to identify anomalies in campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script detects and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and analyzes anomalies in weekly campaign metrics to highlight outliers and trends for marketing performance evaluation.
Purpose:
The Python script identifies and analyzes anomalies in weekly campaign performance metrics over the past eight weeks for Powpow Enterprise Retail.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on deviation levels.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using adjustable thresholds.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level by analyzing weekly data and applying statistical methods to detect outliers.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level for a dental network by analyzing weekly performance data.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
The script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script alerts users when the error rate in revenue processing files exceeds a specified threshold.
Purpose:
The script identifies ads with expired or nearly expired application deadlines across all publishers.
Purpose:
The script identifies and reports anomalies in weekly campaign conversions by analyzing deviations from forecasted metrics.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose
The Python script identifies and reports on campaign performance anomalies by detecting outliers in key metrics using configurable thresholds and generates a weekly report accommodating conversion lag.
Purpose: The Python script compares the CPA (Cost Per Acquisition) for campaigns between the current quarter and the last week, flagging those with a CPA for the last week that...
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script generates a performance anomaly report for pay-per-click marketing campaigns.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Campaigns Anomaly
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
Campaign Performance Anomaly Report with Summary
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
Campaign Performance Anomaly Report with Summary
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds for interquartile range and deviation.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose:
The Python script identifies and reports campaign-level outliers in key conversion metrics, such as Total AMU Sign-Ups and Podcast First Stream, by calculating anomalies using adjustable thresholds.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and calculating deviations using adjustable thresholds.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and rolling up performance metrics to dimensions such as Product Category and Brand/Generic, using adjustable IQR and...
Purpose:
The Python script detects performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts derived from historical trends.
Purpose
Campaign Anomaly Detection
Purpose
Python script solves the problem of generating a performance anomaly report for pay-per-click marketing data.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script checks and filters campaigns based on their budget spending and status, ensuring they meet specific criteria for active traffic allocation.
Purpose:
The Python script identifies anomalies in campaign performance metrics for hotels by using day-of-week forecasts and calculating deviations based on user-defined thresholds.
Purpose:
The Python script identifies duplicate keywords within the same publisher and account, recommends which keywords to pause based on performance metrics, and alerts users via email.
Purpose
Python script to detect anomalies in campaign data and generate an anomaly report.
Purpose
The Python script detects anomalies in campaign performance metrics for different campaign types and accounts.
Purpose
Analyze campaign data to identify anomalies and calculate anomaly scores for each product and account.
Purpose:
The Python script identifies inactive campaigns based on publication costs and predicted user visits within a structured budget allocation framework.
Purpose
This Python script is used to merge data from a primary data source and a reference data source, and then generate an output dataframe.
Category Item Changed - None
Purpose:
The Python script adjusts revenue and conversion data at the keyword level based on latency factors to provide more accurate estimates.
Purpose:
The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds and generating a report for analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The script adjusts revenue and conversion data based on latency factors to provide more accurate estimates.
Purpose:
The Python script identifies outliers in campaign metrics and calculates anomalies using adjustable thresholds to generate a weekly report.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script processes and merges financial data to calculate adjusted publication costs for the latest available date.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in monthly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes and summarizes the performance of marketing strategies by comparing actual results against targets, categorizing them based on management levels, and providing insights for optimization.
Purpose
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and a lookback period.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script attributes quality call conversions to keywords based on their click weight.
Purpose:
The Python script identifies duplicate keywords in advertising campaigns and recommends which ones to pause based on performance metrics.
Purpose:
The Python script processes offline booking data by copying it from a primary data source to an output data frame, allowing for custom output columns.
Purpose:
The Python script processes and exports account data from a primary data source without modifications.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script identifies weekly anomalies in campaign performance metrics using configurable thresholds and generates a summary report.
Purpose: The Python script identifies weekly anomalies in campaign performance metrics by analyzing outliers using configurable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a specified...
Purpose:
The Python script calculates predictive revenue values for campaigns using gross lead data and program-level revenue and conversion rates.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script processes and transforms revenue data from various app store and subscription services to create a structured output for analysis.
Purpose:
The Python script identifies outliers in weekly campaign performance metrics using adjustable thresholds and generates a report accommodating conversion lag.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose: The Python script identifies anomalies in weekly campaign metrics by calculating outliers using adjustable thresholds for interquartile range (IQR) and deviation, focusing on high-traffic campaigns over a configurable lookback...
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose
The script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies outliers in weekly campaign metrics using adjustable thresholds for anomaly detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation.
Purpose:
The Python script identifies and reports anomalies in weekly campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The Python script generates a weekly report to identify anomalies in campaign metrics using configurable thresholds for outlier detection and deviation analysis.
Purpose:
The script processes and merges data from two sources to produce a structured output for wishlist ingestion.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose:
The Python script detects and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script identifies and analyzes anomalies in weekly campaign metrics to highlight outliers and trends for marketing performance evaluation.
Purpose:
The Python script identifies and analyzes anomalies in weekly campaign performance metrics over the past eight weeks for Powpow Enterprise Retail.
Purpose:
The script processes and uploads daily budget data by transforming and deduplicating input records.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on deviation levels.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using adjustable thresholds.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level by analyzing weekly data and applying statistical methods to detect outliers.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level for a dental network by analyzing weekly performance data.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
The script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds for outliers and deviations.
Purpose:
The Python script identifies and reports weekly anomalies in campaign performance metrics using configurable thresholds for outlier detection.
Purpose:
The Python script alerts users when the error rate in revenue processing files exceeds a specified threshold.
Purpose:
The script identifies ads with expired or nearly expired application deadlines across all publishers.
Purpose:
The script identifies and reports anomalies in weekly campaign conversions by analyzing deviations from forecasted metrics.
Purpose:
The Python script identifies and reports conversion anomalies at the campaign level using configurable metrics and thresholds.
Purpose
The Python script identifies and reports on campaign performance anomalies by detecting outliers in key metrics using configurable thresholds and generates a weekly report accommodating conversion lag.
Purpose: The Python script compares the CPA (Cost Per Acquisition) for campaigns between the current quarter and the last week, flagging those with a CPA for the last week that...
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified latency model.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified formula.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script generates a performance anomaly report for pay-per-click marketing campaigns.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Campaigns Anomaly
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies and reports anomalies in weekly campaign performance metrics using configurable thresholds and historical data analysis.
Purpose
Campaign Performance Anomaly Report with Summary
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose
Campaign Performance Anomaly Report with Summary
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds for interquartile range and deviation.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against forecasted values using statistical methods.
Purpose:
The Python script identifies anomalies in campaign performance by comparing actual metrics against day-of-week forecasts using adjustable thresholds.
Purpose:
The Python script identifies and reports campaign-level outliers in key conversion metrics, such as Total AMU Sign-Ups and Podcast First Stream, by calculating anomalies using adjustable thresholds.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and calculating deviations using adjustable thresholds.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The Python script identifies performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
This Python script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose:
The script identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose
Python script that identifies performance anomalies in PPC campaigns by comparing actual data against forecasts based on historical trends.
Purpose The Python script identifies anomalies in campaign performance by analyzing day-of-week forecasts and rolling up performance metrics to dimensions such as Product Category and Brand/Generic, using adjustable IQR and...
Purpose:
The Python script detects performance anomalies in pay-per-click (PPC) campaigns by comparing actual data against forecasts derived from historical trends.
Purpose
Campaign Anomaly Detection
Purpose
Python script solves the problem of generating a performance anomaly report for pay-per-click marketing data.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups based on a specific date range.
Purpose:
The Python script identifies and filters paused CCT groups with single-word keywords based on a specific date range.
Purpose:
The Python script checks and filters campaigns based on their budget spending and status, ensuring they meet specific criteria for active traffic allocation.
Purpose:
The Python script identifies anomalies in campaign performance metrics for hotels by using day-of-week forecasts and calculating deviations based on user-defined thresholds.
Purpose:
The Python script identifies duplicate keywords within the same publisher and account, recommends which keywords to pause based on performance metrics, and alerts users via email.
Purpose
Python script to detect anomalies in campaign data and generate an anomaly report.
Purpose
The Python script detects anomalies in campaign performance metrics for different campaign types and accounts.
Purpose
Analyze campaign data to identify anomalies and calculate anomaly scores for each product and account.
Purpose:
The Python script identifies inactive campaigns based on publication costs and predicted user visits within a structured budget allocation framework.
Purpose
This Python script is used to merge data from a primary data source and a reference data source, and then generate an output dataframe.
Category Item Changed - Product Group
Purpose
The script automates the process of setting all active Google Product Groups to Bid Override with no end date.
Category Linked Datasource - FTP/Email Feed
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The script pauses ad groups with fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The Python script pauses ad groups with over 100 clicks that have not generated any Prime Starts/Conversions in the past 30 days, ensuring they have been active for at...
Purpose:
The script pauses keywords with 0 conversions and 60+ clicks in the last 60 days, ensuring they have been active for at least 60 days.
Purpose:
The Python script pauses ad groups that have received fewer than 10 clicks in the last 60 days, provided they have been active for at least 60 days.
Purpose: The script pauses ad groups with over 100 clicks that have not generated any conversions in the past 30 days, provided they have been active for at least 30...
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script analyzes and summarizes the performance of marketing strategies by comparing actual results against targets, categorizing them based on management levels, and providing insights for optimization.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on their deviation from the target.
Purpose:
The Python script processes offline booking data by copying it from a primary data source to an output data frame, allowing for custom output columns.
Purpose:
The Python script processes and exports account data from a primary data source without modifications.
Purpose:
The Python script processes and transforms revenue data from various app store and subscription services to create a structured output for analysis.
Purpose:
The script processes and merges data from two sources to produce a structured output for wishlist ingestion.
Purpose:
The script processes and uploads daily budget data by transforming and deduplicating input records.
Purpose:
The Python script analyzes marketing strategy performance by comparing actual results against targets and categorizes them based on deviation levels.
Purpose:
The Python script alerts users when the error rate in revenue processing files exceeds a specified threshold.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified latency model.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified formula.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics.
Purpose:
The script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets for Google Smart Bidding strategies.
Purpose:
The Python script analyzes campaign-level forecasts to identify profit-maximizing targets and generates a bulk sheet to update these targets, specifically supporting Google Smart Bidding strategies.
Category Action Type - Revenue Upload
Purpose:
The Python script adjusts revenue and conversion data at the keyword level based on latency factors to provide more accurate estimates.
Purpose:
The script adjusts revenue and conversion data based on latency factors to provide more accurate estimates.
Purpose:
The Python script processes and merges financial data to calculate adjusted publication costs for the latest available date.
Purpose:
The Python script attributes quality call conversions to keywords based on their click weight.
Purpose:
The script processes and merges data from two sources to produce a structured output for wishlist ingestion.
Purpose:
The script processes and uploads daily budget data by transforming and deduplicating input records.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified latency model.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics based on a specified formula.
Purpose:
The Python script processes GEM data to apply a latency curve adjustment for conversion and revenue metrics.
Category Reference Datasource - M1 Report
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
Purpose:
The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
Purpose:
The script updates campaign-level posting statuses by mapping strategies to specific budget and bid dimensions.
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
Purpose:
The script updates campaign-level posting status by mapping strategy-specific data from a reference dataset to an input dataset.
Purpose:
The Python script processes and merges financial data to calculate adjusted publication costs for the latest available date.
Purpose
The Python script maps Salesforce (SFDC) input data to a structured format for further analysis and reporting.
Purpose:
The Python script attributes quality call conversions to keywords based on their click weight.
Purpose:
The script identifies conflicting keywords between current and negative keyword lists in an account.
Category Action Type - Revenue Upload (Preview)
Purpose:
The Python script processes offline booking data by copying it from a primary data source to an output data frame, allowing for custom output columns.
Purpose:
The Python script processes and exports account data from a primary data source without modifications.
Purpose:
The Python script processes and transforms revenue data from various app store and subscription services to create a structured output for analysis.
![Script 1277: [Demo] Ingest Media Plan](/marinone-scripts/assets/images/m1-icon-grey.png){kind=icon}