Script 959: Bidding Strategy Assignment

Purpose:

The script automates the assignment of bidding strategies to campaigns based on their creation date.

To Elaborate

The Python script is designed to automate the assignment of bidding strategies to marketing campaigns based on their age. Specifically, it assigns a “Data Gathering” strategy to campaigns that are less than or equal to seven days old and a “Performance Bidding” strategy to those older than seven days. This approach allows for initial data collection during the early stages of a campaign, followed by a shift to performance optimization once sufficient data has been gathered. The script also updates a “Folder Check” column to indicate whether a campaign has been moved to the performance phase, marking it with “YES” if it has been active for more than seven days.

Walking Through the Code

  1. Data Preparation
    • The script begins by copying the input DataFrame to avoid modifying the original data.
    • It converts the ‘Campaign Creation Date’ column into datetime objects to facilitate date comparisons.
  2. Strategy Assignment Logic
    • The script iterates over each row of the DataFrame, checking the difference between today’s date and the campaign’s creation date.
    • If the campaign is within seven days of its creation, it assigns the “Data Gathering” strategy and leaves the “Folder Check” column blank.
    • If the campaign is older than seven days, it assigns the “Performance Bidding” strategy and marks the “Folder Check” column with “YES”.
  3. Output
    • The modified DataFrame is returned, reflecting the updated strategies and folder check statuses for each campaign.

Vitals

  • Script ID : 959
  • Client ID / Customer ID: 1306917413 / 69058
  • Action Type: Bulk Upload
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Strategy, Folder Check
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Jeremy Brown (jbrown@marinsoftware.com)
  • Created by Jeremy Brown on 2024-04-11 09:59
  • Last Updated by Jeremy Brown on 2024-04-11 09:59
> See it in Action

Python Code

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##
## name: Bidding Strategy Assignment
## description:
##
## The Script automatically assigns a campaign to an Impression Share Strategy called 'Data Gathering' for the first 7 days after being created. Then after the campaign has been live for 7 days it is moved to a CPA strategy called 'Performance Bidding'. The logic is as follows;
## When a campaign's creation date is within 7 days of today's date, it is assigned to "Data Gathering" with a blank Folder Check column (""). Otherwise, it's assigned to "Performance Bidding" with a "YES" in the Folder Check column.
## 
## author: Jeremy Brown
## created: 2024-04-11
## 

today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_STRATEGY = 'Strategy'
RPT_COL_CAMPAIGN_CREATION_DATE = 'Campaign Creation Date'
RPT_COL_FOLDER_CHECK = 'Folder Check'
RPT_COL_IMPR = 'Impr.'

def process(inputDf):
    # Make a copy of the input DataFrame
    outputDf = inputDf.copy()
    
    # Get today's date in the specified timezone
    today_date = datetime.datetime.now(CLIENT_TIMEZONE).date()
    
    # Convert 'Campaign Creation Date' column to datetime objects (assuming format dd/mm/yyyy)
    outputDf['Campaign Creation Date'] = pd.to_datetime(outputDf['Campaign Creation Date'], format='%d/%m/%Y')
    
    # Determine the strategy and folder check based on the campaign creation date
    for index, row in outputDf.iterrows():
        creation_date = row['Campaign Creation Date'].date()
        if (today_date - creation_date).days <= 7:
            # Within 7 days of today's date
            outputDf.at[index, 'Strategy'] = "Data Gathering"
            outputDf.at[index, 'Folder Check'] = ""  # Leave Folder Check blank
        else:
            # More than 7 days old
            outputDf.at[index, 'Strategy'] = "Performance Bidding"
            outputDf.at[index, 'Folder Check'] = "YES"
    
    # Debugging: Print changes made to outputDf
    print("Data Changed:")
    print(outputDf[['Account', 'Campaign', 'Strategy', 'Folder Check']])
    
    return outputDf

# Process the DataFrame
outputDf = process(inputDf)

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

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