Script 1547: Script Campaigns Pause if Cost gets to 98% of the Daily Budget

Purpose:

The script automates the process of pausing and reactivating advertising campaigns based on their daily budget utilization.

To Elaborate

The Python script is designed to manage advertising campaigns by automatically pausing those that have spent 98% or more of their daily budget and reactivating them if they were paused on a previous day. This ensures that campaigns do not exceed their allocated daily budget, thereby optimizing budget allocation and preventing overspending. The script processes a DataFrame containing campaign data, checks each campaign’s spending against its daily budget, and updates the campaign’s status accordingly. It also considers whether a campaign should remain paused or be reactivated based on the date it was paused. This automation helps in maintaining efficient budget management and ensures that campaigns are only paused when necessary, allowing for better control over advertising expenditures.

Walking Through the Code

  1. Initialization:
    • The script initializes an empty DataFrame outputDf to store the results of the campaign processing.
    • It defines a function pause_campaigns to iterate over each campaign in the input DataFrame.
  2. Pausing Campaigns:
    • For each campaign, it checks if the publication cost is at least 98% of the daily budget.
    • If the campaign is enabled and meets the budget threshold, it is paused, and relevant details are added to outputDf.
    • If the campaign does not meet the threshold, it remains active, and existing pause details are carried over.
  3. Reactivating Campaigns:
    • The reactivate_campaigns function checks if a paused campaign’s pause date is not today.
    • If so, the campaign is reactivated, and the pause date is cleared.
  4. Processing Campaigns:
    • The process_campaigns function orchestrates the pausing and reactivating of campaigns.
    • It first calls pause_campaigns to update the campaign statuses based on budget utilization.
    • Then, it calls reactivate_campaigns to ensure campaigns paused on previous days are reactivated if applicable.
    • Finally, it prints the updated DataFrame for review or further processing.

Vitals

  • Script ID : 1547
  • Client ID / Customer ID: 1306928253 / 60270461
  • Action Type: Bulk Upload (Preview)
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Status, Campaign Script Pause Date, CCT_override
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Grégory Pantaine (gpantaine@marinsoftware.com)
  • Created by Grégory Pantaine on 2024-11-27 14:46
  • Last Updated by Grégory Pantaine on 2024-12-05 14:07
> See it in Action

Python Code

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# Get today's date for comparison
today = datetime.datetime.now().date()

# Assuming the input data source (inputDf) and columns as described
# Primary data source and columns
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'
RPT_COL_DAILY_BUDGET = 'Daily Budget'
RPT_COL_PUB_COST = 'Pub. Cost €'
RPT_COL_CONV_CCTSOURCETEMPLATE = 'CCT_sourcetemplate'


# Output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_STATUS = 'Status'
BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE = 'Campaign Script Pause Date'
BULK_COL_CCTOVERRIDE = 'CCT_override'


# Assuming you have inputDf which is a DataFrame loaded from your data source
# Here we initialize the output DataFrame with the same columns
outputDf = pd.DataFrame(columns=[BULK_COL_ACCOUNT, BULK_COL_CAMPAIGN, BULK_COL_STATUS, BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE,BULK_COL_CCTOVERRIDE])

# Function to pause campaigns that are within 2% of their daily budget
def pause_campaigns(inputDf):
    for index, row in inputDf.iterrows():
        campaign = row[RPT_COL_CAMPAIGN]
        account = row[RPT_COL_ACCOUNT]
        status = row[RPT_COL_CAMPAIGN_STATUS]
        daily_budget = row[RPT_COL_DAILY_BUDGET]
        pub_cost = row[RPT_COL_PUB_COST]

        # Skip campaigns that haven't spent enough (less than 98% of daily budget)
        if pub_cost < daily_budget * 0.98:
            continue

        # Pause the campaign if cost is within 2% of the daily budget
        if status == "ENABLED" and pub_cost >= daily_budget * 0.98:
            # Add the paused campaign with today's date for pause dimension
            outputDf.loc[len(outputDf)] = {
                BULK_COL_ACCOUNT: account,
                BULK_COL_CAMPAIGN: campaign,
                BULK_COL_STATUS: 'PAUSED',
                BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE: today,
                # Set CCT_override to "true" only when CCT_sourcetemplate is blank
                BULK_COL_CCTOVERRIDE: "" if pd.isna(row[RPT_COL_CONV_CCTSOURCETEMPLATE]) else "True"
            }
        else:
            # Keep the campaign active and carry over any existing pause date
            outputDf.loc[len(outputDf)] = {
                BULK_COL_ACCOUNT: account,
                BULK_COL_CAMPAIGN: campaign,
                BULK_COL_STATUS: 'ACTIVE',
                BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE: row.get(BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE, ''),
                BULK_COL_CCTOVERRIDE: ''
            }

    return outputDf

# Function to reactivate campaigns if the "Campaign Script Pause Date" is not today
def reactivate_campaigns(inputDf):
    for index, row in inputDf.iterrows():
        pause_date = row[BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE]
        campaign = row[BULK_COL_CAMPAIGN]

        # Reactivate the campaign if it was paused and the pause date is not today
        if pause_date != today and row[BULK_COL_STATUS] == 'PAUSED':
            # Reactivate campaign
            inputDf.at[index, BULK_COL_STATUS] = 'ACTIVE'
            inputDf.at[index, BULK_COL_CAMPAIGN_SCRIPT_PAUSE_DATE] = ''  # Clear pause date

    return inputDf

# Main function to process the campaigns
def process_campaigns(inputDf):
    # Pause campaigns based on the 98% budget threshold
    outputDf = pause_campaigns(inputDf)

    # Reactivate campaigns that were paused on previous days
    outputDf = reactivate_campaigns(outputDf)

    # Print the output for review
    print(outputDf)

    # Optionally, this outputDf can be sent back to your system or API for updating the campaigns

# Now, you can simply call the function `process_campaigns(inputDf)` where you load the inputDf.

Post generated on 2025-03-11 01:25:51 GMT

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