Script 943: 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 advertising campaigns based on their age. Specifically, it assigns a campaign to an “Impression Share Strategy” called ‘Data Gathering’ if the campaign is within the first 7 days of its creation. After the campaign has been live for more than 7 days, it is moved to a “CPA strategy” called ‘Performance Bidding’. This transition is marked by a change in the ‘Folder Check’ column from blank to “YES”. The script processes a DataFrame containing campaign data, evaluates each campaign’s creation date, and updates the strategy and folder check status accordingly. This automation helps streamline the management of campaign strategies, ensuring that newer campaigns focus on data gathering while older ones optimize for performance.
Walking Through the Code
- Data Preparation
- The script begins by copying the input DataFrame to avoid altering the original data.
- It converts the ‘Campaign Creation Date’ column to datetime objects to facilitate date comparisons.
- Strategy Assignment Logic
- The script iterates over each row in the DataFrame.
- For each campaign, it calculates the number of days since its creation.
- If the campaign is 7 days old or less, it assigns the ‘Data Gathering’ strategy and leaves the ‘Folder Check’ column blank.
- If the campaign is older than 7 days, it assigns the ‘Performance Bidding’ strategy and sets the ‘Folder Check’ column to “YES”.
- Output
- The script prints the changes made to the DataFrame for verification purposes.
- Finally, it returns the modified DataFrame with updated strategies and folder check statuses.
Vitals
- Script ID : 943
- Client ID / Customer ID: 1306926013 / 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 09:45
- Last Updated by Jeremy Brown on 2024-04-11 09:45
> 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 2024-11-27 06:58:46 GMT