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 profiling refers to creating detailed profiles that represent the behaviors and preferences of users, and segmentation divides the user base into distinct groups with common characteristics, making it easier to target specific segments with personalized marketing, products, or services.
# User Segmentation_Online Retail Data ## Ikhtisar Proyek ini bertujuan untuk melakukan segmentasi pengguna menggunakan data retail online. Dengan menggunakan teknik RFM (Recency, Frequency, Monetary) dan analisis data, kami mengidentifikasi berbagai segmen pelanggan untuk membantu dalam meningkatkan retensi pelanggan dan strategi pemasaran.
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.
User segmentation using a sort of classifiers (some quite uncommon like the Fuzzy K-Nearest Neighbours).
In-app survey SDK for Web, iOS, and Android.
Introducing the Ultimate A/B Testing and Experiment Analysis Dataset! 👀
Rule-Based User Segmentation
My 'Out of PM scopes' data project
User segmentation API
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