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Personalization for Pentathlon

UCSD · Customer Analytics

Designed and implemented a multi-channel personalization engine that tailored recommendations and messaging across the customer lifecycle. Used segmentation models to identify distinct user cohorts and deliver contextually relevant offers at each touchpoint.

Approach

Combined collaborative filtering with behavioral segmentation to create personalized experiences across email, in-app, and ad channels. The system adapted messaging based on where each user sat in their lifecycle journey.

Tools & Technologies

PythonScikit-learnRecommendation AlgorithmsSegmentation

Topics

PersonalizationSegmentationRecommendation SystemsPython
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