Purpose:

The Python script pauses keywords with more than 10 clicks and a conversion rate below 10%.

To Elaborate

The script is designed to manage online advertising campaigns by pausing specific keywords that are underperforming. It targets keywords that have received more than 10 clicks but have a conversion rate of less than 10%. The script updates the status of these keywords to “PAUSED” and records the date of this action. This helps in optimizing the advertising budget by stopping investment in keywords that do not convert well, thus allowing for better allocation of resources towards more effective keywords. Additionally, the script checks if a specific template field is blank and sets an override flag accordingly, which might be used for further processing or reporting.

Walking Through the Code

1. Initialization and Setup
   • The script begins by defining a dictionary for match types, which categorizes keywords into ‘exact’, ‘phrase’, or ‘broad’.
   • It retrieves the current date, which is used later to mark when a keyword is paused.
2. Data Preparation
   • The script reads data from a primary data source into a DataFrame named inputDf.
   • It defines several constants representing column names for both input and output data, which are used to manipulate and access specific data fields.
3. Processing and Business Logic
   • A copy of the input DataFrame is created for output purposes, where the status of all keywords is initially set to “PAUSED”.
   • The script sets the “Script Pause Date” column to the current date for all entries.
   • It checks if the ‘CCT_sourcetemplate’ column is blank and sets the ‘CCT_override’ column to “True” if it is not blank, otherwise it remains empty.
4. Output and Debugging
   • The script prints the first few rows of the input DataFrame for verification purposes, although this is primarily for debugging and not part of the core functionality.

Vitals

• Script ID : 1541
• Client ID / Customer ID: 1306928253 / 60270461
• Action Type: Bulk Upload (Preview)
• Item Changed: Keyword
• Output Columns: Account, Campaign, Group, Keyword, Match Type, Status, Script Pause Date, CCT_override
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: Grégory Pantaine (gpantaine@marinsoftware.com)
• Created by Grégory Pantaine on 2024-11-27 14:16
• Last Updated by Grégory Pantaine on 2024-12-04 16:21

> See it in Action

Python Code

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##
## name: Script: Clicks > 10 & Conversion Rate <10% = PAUSE
## description: Pause any keywords visible in this Script and set the dimension "Script Pause Date" to today's date.
##  
## 
## author: ChatGPT, Marin Scripts & Gregory Pantaine.
## created: 2024-11-27
## 

MATCH_TYPE = {
  'EXACT': 'exact',
  'PHRASE': 'phrase',
  'BROAD': 'broad',
}
today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_KEYWORD = 'Keyword'
RPT_COL_STATUS = 'Status'
RPT_COL_MATCH_TYPE = 'Match Type'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_GROUP = 'Group'
RPT_COL_IMPR = 'Impr.'
RPT_COL_CLICKS = 'Clicks'
RPT_COL_PUB_COST = 'Pub. Cost €'
RPT_COL_CTR = 'CTR %'
RPT_COL_AVG_CPC = 'Avg. CPC €'
RPT_COL_IMPR_SHARE = 'Impr. share %'
RPT_COL_CONV = 'Conv.'
RPT_COL_COST_PER_CONV = 'Cost/Conv. €'
RPT_COL_CONV_RATE = 'Conv. Rate %'
RPT_COL_CONV_CCTSOURCETEMPLATE = 'CCT_sourcetemplate'

# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_KEYWORD = 'Keyword'
BULK_COL_MATCH_TYPE = 'Match Type'
BULK_COL_STATUS = 'Status'
BULK_COL_SCRIPT_PAUSE_DATE = 'Script Pause Date'
BULK_COL_CCTOVERRIDE = 'CCT_override'


# Initialize output DataFrame
outputDf = inputDf.copy()
outputDf[BULK_COL_STATUS] = "PAUSED"
outputDf[BULK_COL_SCRIPT_PAUSE_DATE] = today.strftime('%Y-%m-%d')

# Set CCT_override to "true" only when CCT_sourcetemplate is blank
outputDf[BULK_COL_CCTOVERRIDE] = outputDf[RPT_COL_CONV_CCTSOURCETEMPLATE].isna().map({True: "", False: "True"})

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

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