Script 113: Strategy Assignment
Purpose:
The Python script assigns marketing campaigns to specific strategies based on campaign name, creation date, and accumulated clicks.
To Elaborate
The script is designed to automate the assignment of marketing campaigns to predefined strategies. It evaluates each campaign based on its name, creation date, and the number of clicks it has accumulated. The script applies a set of business rules to determine the appropriate strategy for each campaign. These rules include checking for specific tokens in the campaign name to assign initial strategies, adjusting strategies for campaigns older than 14 days with significant engagement, and reassigning strategies for campaigns that have been active for more than 60 days. The goal is to ensure that campaigns are aligned with the most suitable strategy to optimize their performance and resource allocation.
Walking Through the Code
- Initialization and Setup
- The script begins by defining constants for column names and strategies. These constants are used throughout the script to reference specific data fields and strategy values.
- Strategies are predefined and mapped to specific values, such as “SVOD - MY - Title_Exc-Launch - TIS” for exclusive campaigns.
- Rule 1: Strategy Assignment Based on Campaign Name
- The script checks if the campaign name contains specific tokens (“_ Exc” or “_ NonExc”) to assign initial strategies. This is done using a case-insensitive search.
- Campaigns with “_ Exc” are assigned the “Exc-Launch” strategy, while those with “_ NonExc” are assigned the “NonExc-Launch” strategy.
- Rule 2: Strategy Adjustment for Older Campaigns with High Engagement
- Campaigns that are more than 14 days old and have accumulated at least 100 clicks are reassigned to the “CPA BAU” strategy.
- This rule applies to both exclusive and non-exclusive campaigns, ensuring that high-engagement campaigns are managed under a business-as-usual strategy.
- Rule 3: Evergreen Strategy for Long-Running Campaigns
- Campaigns that have been active for more than 60 days are assigned to the “CPA Evergreen” strategy.
- This rule ensures that long-running campaigns are transitioned to a strategy that focuses on sustained performance.
- Output Preparation
- The script identifies campaigns with changed strategies and prepares an output DataFrame containing only these campaigns.
- If no campaigns have changed strategies, an empty output DataFrame is prepared.
Vitals
- Script ID : 113
- Client ID / Customer ID: 1306924439 / 69058
- Action Type: Bulk Upload
- Item Changed: Campaign
- Output Columns: Account, Campaign, Strategy
- Linked Datasource: M1 Report
- Reference Datasource: None
- Owner: Jeremy Brown (jbrown@marinsoftware.com)
- Created by Jeremy Brown on 2023-05-19 11:07
- Last Updated by Jonathan Reichl on 2023-12-13 11:19
> See it in Action
Python Code
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#
# Assign Campaign to Strategy according to:
# - Campaign Name
# - Campaign Creation Date
# - accumulated clicks
#
# Author: Michael S. Huang
# Date: 2023-05-18
#
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_STRATEGY = 'Strategy'
RPT_COL_CAMPAIGN_CREATIONDATE = 'Campaign Creation Date'
RPT_COL_CLICKS = 'Clicks'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_STRATEGY = 'Strategy'
outputDf[BULK_COL_STRATEGY] = "<<YOUR VALUE>>"
# define Strategies to map to
VAL_STRATEGY_IS_EXC = "SVOD - MY - Title_Exc-Launch - TIS"
VAL_STRATEGY_IS_NON_EXC = "SVOD - MY - Title_NonExc-Launch - TIS"
VAL_STRATEGY_CPA_BAU = "SVOD - MY - Title-BAU - CPS"
VAL_STRATEGY_CPA_EVERGREEN = "SVOD - MY - Title-Evergreen - CPS"
# define campaign tokens to match
VAL_CAMPAIGN_NAME_TOKEN_EXC = "_ Exc"
VAL_CAMPAIGN_NAME_TOKEN_NON_EXC = "_ NonExc"
# defines dates to check
print("timezone", CLIENT_TIMEZONE)
today = datetime.datetime.now(CLIENT_TIMEZONE).date()
date_14_days_ago = pd.to_datetime(today - datetime.timedelta(days=14))
date_60_days_ago = pd.to_datetime(today - datetime.timedelta(days=60))
print(today, date_14_days_ago, date_60_days_ago)
# define tmp column for new Strategy and set to empty
TMP_STRATEGY = RPT_COL_STRATEGY + '_'
inputDf[TMP_STRATEGY] = np.nan
### Rule 1: Assign to Exc/NonExc Strategy based on token in campaign name
### case insensitive
inputDf.loc[ inputDf[RPT_COL_CAMPAIGN].str.contains(VAL_CAMPAIGN_NAME_TOKEN_EXC, case=False), \
TMP_STRATEGY \
] = VAL_STRATEGY_IS_EXC
inputDf.loc[ inputDf[RPT_COL_CAMPAIGN].str.contains(VAL_CAMPAIGN_NAME_TOKEN_NON_EXC, case=False), \
TMP_STRATEGY \
] = VAL_STRATEGY_IS_NON_EXC
### Rule 2: if Exc/NonExc campaign created more than 14 days ago and clicks >= 100,
### assign to CPA BAU
inputDf.loc[ ( inputDf[RPT_COL_CAMPAIGN].str.contains(VAL_CAMPAIGN_NAME_TOKEN_EXC, case=False) | \
inputDf[RPT_COL_CAMPAIGN].str.contains(VAL_CAMPAIGN_NAME_TOKEN_NON_EXC, case=False) ) & \
(inputDf[RPT_COL_CAMPAIGN_CREATIONDATE] <= date_14_days_ago) & \
(inputDf[RPT_COL_CLICKS] >= 100), \
TMP_STRATEGY \
] = VAL_STRATEGY_CPA_BAU
### Rule 3: if campaign created more than 60 days ago,
### assign to CPA Evergreen
inputDf.loc[ (inputDf[RPT_COL_CAMPAIGN_CREATIONDATE] <= date_60_days_ago), \
TMP_STRATEGY \
] = VAL_STRATEGY_CPA_EVERGREEN
# find changed campaigns
changed = inputDf[TMP_STRATEGY].notnull() & (inputDf[RPT_COL_STRATEGY] != inputDf[TMP_STRATEGY])
# put changed campaigns into outputDf; if none, prepare empty outputDf
if sum(changed) > 0:
print("== Campaigns with Changed Strategy ==", tableize(inputDf.loc[changed]))
# only select changed rows
cols = [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, TMP_STRATEGY]
outputDf = inputDf.loc[ changed, cols ].copy() \
.rename(columns = { \
TMP_STRATEGY: BULK_COL_STRATEGY \
})
print("outputDf", tableize(outputDf))
else:
print("Empty outputDf")
outputDf = outputDf.iloc[0:0]
Post generated on 2025-03-11 01:25:51 GMT