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.

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_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.

🧠 Case study on data preprocessing and behavioral analysis of TechnoMagicLand visitors. Includes clustering, correlation, and visualization in R, with focus on identifying repeat visitors and improving engagement strategies.

Rule-Based User Segmentation

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! 👀

This funnel analysis project focused on identifying user drop-off points in a newly launched sign-up experience and delivering actionable insights to improve conversion and activation rates.

My 'Out of PM scopes' data project

사이드 프로젝트로 진행한 음식 배달 앱 로그 데이터 분석 프로젝트입니다.

User segmentation API