Purpose:

The script pauses advertisements if they have zero conversions after spending $100.

To Elaborate

The Python script is designed to manage advertising campaigns by automatically pausing ads that have not generated any conversions after spending a specified amount of money, in this case, $100. This is a cost-control measure to ensure that advertising budgets are not wasted on ineffective ads. The script processes data from a primary data source, evaluates the performance of each ad, and updates their status to ‘PAUSE’ if they meet the criteria of zero conversions after the specified spend threshold. This helps in optimizing the allocation of advertising budgets by focusing on more effective ads.

Walking Through the Code

1. Data Preparation:
   • The script begins by defining the primary data source and the relevant columns needed for processing, such as account, campaign, group, creative ID, and status.
   • A temporary column is created to store the new status of each ad, initialized to ‘PAUSE’.
2. Data Processing:
   • The script selects the necessary columns from the input data frame and creates a copy of this subset.
   • It renames the temporary status column to match the output column format.
3. Output:
   • The processed data frame, which now includes the updated status for each ad, is printed in a tabular format for review.

Vitals

• Script ID : 745
• Client ID / Customer ID: 1306925431 / 60269477
• Action Type: Bulk Upload (Preview)
• Item Changed: Ad
• Output Columns: Account, Campaign, Group, Creative ID, Status
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: Byron Porter (bporter@marinsoftware.com)
• Created by Byron Porter on 2024-03-06 20:07
• Last Updated by Byron Porter on 2024-03-06 20:11

> See it in Action

Python Code

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##
## name: Golden Hippo - Pause Ads - Conversions
## description:
##  Pauses ads if 0 conversions after $100 in spend
## 
## author: 
## created: 2024-03-06
## 


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

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_GROUP = 'Group'
RPT_COL_CREATIVE_ID = 'Creative ID'
RPT_COL_STATUS = 'Status'
RPT_COL_TABOOLA_COST_PER_CONV = 'Taboola Cost/Conv $'

# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_CREATIVE_ID = 'Creative ID'
BULK_COL_STATUS = 'Status'


# user code start here
# create temp column to store new status and default to empty
TMP_STATUS = RPT_COL_STATUS + '_'
inputDf[TMP_STATUS] = 'PAUSE'

cols = [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_GROUP, RPT_COL_CREATIVE_ID, TMP_STATUS]
outputDf = inputDf.loc[ :, cols ].copy() \
                    .rename(columns = { \
                        TMP_STATUS: BULK_COL_STATUS \
                    })

print(tableize(outputDf))

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