Purpose

The Python script identifies campaigns where the previous day’s spending is at least 90% of the daily budget and flags them for budget capping.

To Elaborate

The script is designed to monitor advertising campaigns by analyzing their spending relative to their daily budget. It specifically identifies campaigns where the publisher cost for the previous day reaches or exceeds 90% of the allocated daily budget. Additionally, it considers the ‘iDNE’ metric, ensuring it is less than 1.5, and checks if the ‘Lost Impression Share’ is greater than 10%. If these conditions are met, the campaign is flagged with a “Budget Capped” alert. This process helps in managing and optimizing campaign budgets by highlighting those that are at risk of overspending, allowing for timely adjustments to prevent budget overruns.

Walking Through the Code

1. Data Preparation
   • The script begins by converting the ‘iDNE’ column in the input DataFrame to numeric values, handling any conversion errors by coercing them to NaN. This ensures that subsequent calculations involving ‘iDNE’ are performed correctly.
2. Calculation of Ratios and Conditions
   • It calculates the ratio of the publisher cost to the daily budget for each campaign and stores it in a new column ‘Pub Cost / Budget’.
   • The script retains the ‘iDNE’ and ‘Lost Impression Share’ values for further analysis.
3. Budget Cap Alert Logic
   • A threshold of 0.90 is set, which can be adjusted by the user as needed.
   • The script checks if the ‘Pub Cost / Budget’ is below this threshold and clears any existing budget alerts.
   • If the ‘Pub Cost / Budget’ is equal to or exceeds the threshold, ‘iDNE’ is less than 1.5, and ‘Lost Impression Share’ is greater than 10%, it flags the campaign with a “Budget Capped” alert.
4. Output Preparation
   • The modified DataFrame is printed, and a new DataFrame is created containing only the relevant columns: ‘Account’, ‘Campaign’, and ‘Budget Alert’, which is then prepared for output.

Vitals

• Script ID : 859
• Client ID / Customer ID: 197178269 / 13095968
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, Budget Alert
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: smalina@marinsoftware.com (smalina@marinsoftware.com)
• Created by Stephen Malina on 2024-03-27 21:36
• Last Updated by Stephen Malina on 2024-04-23 20:46

> See it in Action

Python Code

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#
# Tag campaign if Pub Cost for prior day is 90% of Daily Budget
#
#
# Author: Stephen Malina
# Date: 2024-03-27

RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_PUB_COST = 'Pub. Cost $'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_DAILY_BUDGET = 'Daily Budget'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'
RPT_COL_BUDGET_ALERT = 'Budget Alert'
RPT_COL_iDNE = 'iDNE'
RPT_COL_LOST_IMP_SHARE = 'Lost Impr. Share (Budget) %'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_BUDGET_ALERT = 'Budget Alert'

# Convert the 'iDNE' column to numeric values
inputDf[RPT_COL_iDNE] = pd.to_numeric(inputDf[RPT_COL_iDNE], errors='coerce')

# Calculate the difference between daily budget and pub cost, include iDNE for consideration
inputDf['Pub Cost / Budget'] = inputDf[RPT_COL_PUB_COST] / inputDf[RPT_COL_DAILY_BUDGET]
inputDf['iDNE'] = inputDf[RPT_COL_iDNE]
inputDf['Lost Imp Share'] = inputDf[RPT_COL_LOST_IMP_SHARE]

# Output a "Budget Cap Alert" where daily spend is greater than 90% of daily budget and iDNE is less than 1.5
threshold = 0.90  # Adjust this threshold as needed
inputDf.loc[inputDf['Pub Cost / Budget'] < threshold, BULK_COL_BUDGET_ALERT] = ""
inputDf.loc[(inputDf['Pub Cost / Budget'] >= threshold) & (inputDf['iDNE'] < 1.5) & (inputDf['Lost Imp Share'] > 10), BULK_COL_BUDGET_ALERT] = "Budget Capped"

# Print the modified inputDf
print(inputDf)
cols = [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, BULK_COL_BUDGET_ALERT]
outputDf = inputDf[cols]

Post generated on 2024-11-27 06:58:46 GMT