Customer Churn Analysis

This project analyzes customer churn in a telecommunications dataset to identify the main factors influencing customer retention and churn behavior.

The analysis explores churn patterns across different dimensions including customer demographics, contract types, and service usage levels. Using Excel pivot analysis and visualization, the project identifies high-risk customer segments and key drivers behind churn.

The findings highlight that senior customers, month-to-month contracts, and low-usage customers have higher churn rates. These insights can help businesses design better retention strategies.

Tools Used:

Excel, Data Cleaning, Pivot Tables, Data Visualization