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.

To Elaborate

The Python script is designed to manage ad groups by pausing those that have not met a certain level of engagement. Specifically, it targets ad groups that have received fewer than 10 clicks over the past 60 days, ensuring that these groups have been active for at least 60 days before making any changes. This helps in optimizing ad spend by focusing resources on more effective ad groups. The script processes input data to identify these underperforming groups and updates their status to “PAUSED,” effectively halting their activity until further review or adjustment.

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 a commented-out section intended to shift the header row of the DataFrame if necessary. This ensures that the correct row is used as the header, but it is currently inactive.
3. Column Verification:
   • It checks if the necessary columns (Account, Campaign, Group) exist in the DataFrame after any adjustments. If not, it raises an error.
4. Output DataFrame Creation:
   • If the required columns are present, the script creates a new DataFrame, outputDf, with the same Account, Campaign, and Group columns from the input.
   • It sets the Status and Group Status columns to “PAUSED” for all entries, indicating that these ad groups should be paused.
5. User Changeable Parameters:
   • The script allows for potential adjustments in the header shifting logic and the criteria for pausing ad groups, although these are not explicitly detailed in the current code.

Vitals

• Script ID : 1689
• Client ID / Customer ID: 1306917411 / 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 17:39
• Last Updated by Chris Jetton on 2025-02-07 17:59

> See it in Action

Python Code

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##
## name: pause_inactive_groups
## description:
## Pause ad groups who have seen <10 clicks in the last 60 days (must have been live for 60 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