arpu

Built a SaaS analytics project using SQL and Python where I reconstructed customer lifecycle from snapshot data and analyzed key metrics like MRR, churn, cohort retention, ARPU, and LTV. I found that revenue growth was driven by customer acquisition rather than pricing, as ARPU declined over time while MRR increased

A complete ETL solution with a PostgreSQL database, enabling calculation of key business metrics (KPI) such as revenue, ARPU, LTV, churn, retention, and cohort analysis.

Analizing customer purchase behaviour per cohorts using Online Retail II Dataset from Kaggle.

Mobile Game In-App Purchase Analytics: EDA, Funnel, Cohort Analysis, and ML-based Whale/LTV Prediction models. 데이터 기반의 모바일 게임 인앱 결제(IAP) 최적화 분석. 사용자 세그먼트별 행동 패턴 분석 및 유저 LTV/Whale 예측 모델링 파이프라인

Jupyter notebook analyzing subscription revenue performance based on user transaction data (conversion rate, ARPU, revenue forecast).

Customer retention and revenue analysis using Cohort Analysis, ARPU, and Payback Period with SQL and Python.

Python in use of pandas, numpy, sklearn, statsmodels, gensim, matplotlib, plotly, seaborn, bokeh

The case study is based on how a subscription-based e-commerce business employed customer-centric strategies to reduce churn and increase customer lifetime value. How companies are Maximizing customer spending and loyalty while minimizing subscription cancellations to enhance profits and long-term business sustainability in an e-commerce model.