Campaign Performance Prediction
Two-stage system predicting campaign pipeline potential before launch and monitoring active campaigns daily.
Akash Sharma
Primary Owner
Daily
Campaign Scoring
2-Stage
Architecture
Overview
Two-stage architecture: (1) XGBoost Classifier predicting high vs. low potential campaigns (pipeline threshold classification). (2) XGBoost Regressor estimating expected pipeline value/volume for predicted high-potential campaigns. Features include campaign attributes, budget, type, date-derived features, pipeline context at campaign start, active campaign counts, and historical averages for similar campaigns.
The problem
Marketing teams were reactive; they only knew a campaign underperformed after it ended. They needed forward-looking predictions to decide which campaigns to scale, which to cut, and how to reallocate budget.
Results
Enabled proactive campaign management by predicting success before launch and flagging underperformers for budget reallocation, shifting marketing teams from post-campaign hindsight to forward-looking intelligence.
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