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 days.

To Elaborate

The Python script is designed to manage advertising campaigns by identifying and pausing underperforming ad groups. Specifically, it targets ad groups that have received more than 100 clicks but have not resulted in any conversions, referred to as “Prime Starts/Conv,” in the last 30 days. Additionally, these ad groups must have been active for at least 30 days to be considered for pausing. This process helps in optimizing the budget allocation by ensuring that resources are not wasted on ineffective ad groups. The script processes input data, checks for necessary columns, and outputs a DataFrame with the status of the ad groups updated to “PAUSED.”

Walking Through the Code

1. Data Preparation:
   • The script begins by defining constants for column names related to campaigns, groups, and accounts.
   • It retrieves the primary data source from a dictionary and assigns it to inputDf.
2. Header Adjustment:
   • The script includes commented-out code for shifting the header row if necessary, ensuring the correct data structure.
3. Column Verification:
   • It checks if the required columns (Account, Campaign, Group) are present in the DataFrame after any adjustments.
4. Output DataFrame Creation:
   • If the necessary columns are present, it creates an outputDf DataFrame with the same account, campaign, and group information, setting the status of each group to “PAUSED.”
5. Error Handling:
   • If the expected columns are not found, the script raises a ValueError to alert the user.

Vitals

• Script ID : 1699
• Client ID / Customer ID: 1306926853 / 69058
• Action Type: Bulk Upload
• Item Changed: AdGroup
• Output Columns: Account, Campaign, Group, Status, Group Status
• Linked Datasource: FTP/Email Feed
• Reference Datasource: None
• Owner: Chris Jetton (cjetton@marinsoftware.com)
• Created by Chris Jetton on 2025-02-06 18:42
• Last Updated by Chris Jetton on 2025-02-07 18:09

> See it in Action

Python Code

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##
## name: pause_low_performing_groups
## description:
##  Pause ad groups with 100+ clicks who have not driven any Prime Starts/Conv in the past 30 days (must have been live for 30 days)
## 
## author: 
## created: 2025-02-06
## 

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


RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_GROUP = 'Group'
RPT_COL_ACCOUNT = 'Account'

# primary data source and columns
inputDf = dataSourceDict["1"]
    
# Shift the header row to the correct position

#if len(inputDf) > 5:  # Ensure there are at least 6 rows
    #inputDf.columns = inputDf.iloc[5]  # Set the 6th row as headers
    #inputDf = inputDf[6:].reset_index(drop=True)  # Drop previous rows and reset index
#else:
    #raise ValueError("Input CSV file does not have enough rows to shift headers correctly.")


print("Headers after shifting:", inputDf.columns)

# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_STATUS = 'Status'
BULK_COL_GROUP_STATUS = 'Group Status'
#outputDf[BULK_COL_STATUS] = "<<YOUR VALUE>>"

# user code start here
print(tableize(inputDf.head()))


# Check if the necessary columns exist after the adjustment
if all(col in inputDf.columns for col in [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_GROUP]):
    # Output DataFrame
    outputDf = pd.DataFrame({
        'Account': inputDf[RPT_COL_ACCOUNT],
        'Campaign': inputDf[RPT_COL_CAMPAIGN],
        'Group': inputDf[RPT_COL_GROUP],
        'Status': "PAUSED",
        'Group Status': "PAUSED"
    })
    print(outputDf)
else:
    raise ValueError("The expected columns are not found in the adjusted DataFrame.")

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