Churn Analysis

is project focuses on analyzing customer churn to help a business understand why customers are leaving and what can be done to reduce churn rates. The goal is to identify key factors contributing to customer attrition and suggest strategies to improve retention.

Using a real-world customer dataset (telecom industry, e-commerce, or subscription service), I cleaned and prepared the data, performed exploratory data analysis (EDA), and built visualizations to uncover patterns in customer behavior.

Key metrics analyzed included customer tenure, service usage, complaints, contract type, monthly charges, and payment method. I applied statistical analysis and segmentation techniques to classify high-risk customers and visualize churn trends over time.