Script 25: Strategy Auto Assign on MTD Conv

Script 25: Strategy Auto Assign on MTD Conv

Purpose:

The Python script reassigns advertising strategies to campaigns based on their Month-to-Date conversion levels.

To Elaborate

The Python script is designed to automatically assign advertising strategies to campaigns based on their Month-to-Date (MTD) conversion levels. It uses predefined conversion ranges to determine which strategy should be applied to each campaign. The script evaluates each campaign’s conversion count and assigns a new strategy if the conversion count falls within a specified range. This process helps optimize campaign performance by ensuring that strategies are aligned with current conversion data. The script also identifies campaigns where the strategy has changed and prepares this information for further processing or reporting.

Walking Through the Code

  1. Define Strategy Conversion Ranges:
    • The script begins by defining a dictionary, strategy_campaign_conversion_ranges, which maps strategies to their respective conversion ranges. Each strategy has a minimum and maximum conversion threshold, and if ranges overlap, the last rule takes precedence.
  2. Initialize DataFrames:
    • Two DataFrames, inputDf and outputDf, are used to manage campaign data. A new column, ‘New Strategy’, is added to inputDf to store the reassigned strategy for each campaign.
  3. Apply Conversion Range Rules:
    • The script iterates over each strategy and its conversion range. For each campaign, it checks if the conversion count falls within the specified range and assigns the corresponding strategy to the ‘New Strategy’ column.
  4. Identify Changed Strategies:
    • The script identifies campaigns where the strategy has changed by comparing the original strategy with the newly assigned strategy. It prints out these campaigns for review.
  5. Update Output DataFrame:
    • The ‘New Strategy’ values are copied to the outputDf, which is filtered to include only campaigns with changed strategies. This ensures that only relevant data is prepared for further processing or reporting.

Vitals

  • Script ID : 25
  • Client ID / Customer ID: 309909744 / 14196
  • Action Type: Bulk Upload (Preview)
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Strategy
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Michael Huang (mhuang@marinsoftware.com)
  • Created by Michael Huang on 2023-03-21 09:55
  • Last Updated by Michael Huang on 2023-12-06 04:01
> See it in Action

Python Code

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#
# Assign Campaign to Strategy according to Month-to-Date Conversions 
#
#
# Author: Michael S. Huang
# Date: 2023-01-20

# define strategy conversion ranges 
 # if over-lapping, last rule wins
strategy_campaign_conversion_ranges = {
    # key: strategy, value: (conv min, conv max)
    'Unassigned': (0, 1000),
    'Search - Non-Brand - Budget': (1000, 3000),
    'Search - Top Performers': (3000, 5000),
    'Full Funnel Bidding': (5000, 99999),
}



RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN_ID = 'Campaign ID'
RPT_COL_STRATEGY = 'Strategy'
RPT_COL_CAMPAIGN_TYPE = 'Campaign Type'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'
RPT_COL_DAILY_BUDGET = 'Daily Budget'
RPT_COL_PUB_COST = 'Pub. Cost $'
RPT_COL_COST_PER_CONV = 'Cost/Conv. $'
RPT_COL_ROAS = 'ROAS'
RPT_COL_AVG_CPC = 'Avg. CPC $'
RPT_COL_CONV_RATE = 'Conv. Rate %'
RPT_COL_CTR = 'CTR %'
RPT_COL_CONV = 'Conv.'
RPT_COL_REVENUE = 'Revenue $'
RPT_COL_SEARCH_LOSTTOPISBUDGET = 'Search Lost Top IS (Budget) %'
RPT_COL_SEARCH_LOSTTOPISRANK = 'Search Lost Top IS (Rank) %'
RPT_COL_LOST_IMPRSHAREBUDGET = 'Lost Impr. Share (Budget) %'
RPT_COL_LOST_IMPRSHARERANK = 'Lost Impr. Share (Rank) %'
RPT_COL_AVG_BID = 'Avg. Bid $'
RPT_COL_HIST_QS = 'Hist. QS'
RPT_COL_IMPR = 'Impr.'
RPT_COL_CLICKS = 'Clicks'
RPT_COL_PUBLISHER = 'Publisher'
BULK_COL_STRATEGY = 'Strategy'

outputDf[BULK_COL_STRATEGY] = numpy.nan

# add new column to track new strategy
inputDf['New Strategy'] = numpy.nan

# Apply conversion range rule for each strategy
for strat, (conv_min, conv_max) in strategy_campaign_conversion_ranges.items():
    print("Applying Strategy Conv Range: ", strat, conv_min, conv_max)
    inputDf.loc[ (inputDf[RPT_COL_CONV] >= conv_min) & (inputDf[RPT_COL_CONV] <= conv_max), 'New Strategy'] = strat

# find changed strategies
print("== Campaigns with Remapped Strategy ==")
changed = inputDf[ inputDf['New Strategy'].notnull() & (inputDf[RPT_COL_STRATEGY] != inputDf['New Strategy']) ]
cols = [RPT_COL_CAMPAIGN, RPT_COL_CONV, RPT_COL_STRATEGY, 'New Strategy']
print(changed[cols].to_string())

# copy new strategy to output
outputDf.loc[:,RPT_COL_STRATEGY] = inputDf.loc[:,'New Strategy']

# only include campaigns with changed strategy in bulk file
outputDf = outputDf[ inputDf['New Strategy'].notnull() & (inputDf[RPT_COL_STRATEGY] != inputDf['New Strategy']) ]

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

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