A sample churn prevention solution for an fintech app
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Updated
May 11, 2020 - HTML
A sample churn prevention solution for an fintech app
Wrangling & Modeling of Duolingo Data (48-hour Analysis Challenge)
Clean and Apply RFM technique to rank and group clusters to identify the best customers and perform targeted marketing campaigns, using real online transaction data
User segmentation using a sort of classifiers (some quite uncommon like the Fuzzy K-Nearest Neighbours).
This research study focuses on analyzing user behavior data from Duolingo, a language learning app. The primary objective is to predict user churn using semi-supervised learning techniques.
Rule-Based User Segmentation
My 'Out of PM scopes' data project
User segmentation API
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