A business analysis of a UK-based online store to understand trends in customer behavior and sales in order to improve sales.

This project analyzes customer churn within the telecommunications industry using the IBM Telco dataset. We implemented a dual-modeling approach: 1) A classification analysis using Logistic Regression and Random Forest to predict at-risk customers (achieving an AUC of 0.84), and 2) A linear regression audit to deconstruct the pricing drivers of monthly charges (R² ≈ 0.999). The findings provide actionable insights for targeted customer retention and pricing transparency.