Overview

Embark on a comprehensive journey with the Analyzing Customer Churn Rate case study in Power BI for Databel, where you'll delve into customer data to comprehend and diminish churn. Beginning by ensuring data integrity through the detection of duplicate customer IDs, you'll then convert the "Churn Label" column into a binomial format to accurately calculate churn rates. Exploring churn reasons, you'll craft visualizations to discern common causes and categorize related reasons for clearer insights, all while balancing churn rates by state using maps to avoid skewed perceptions. From demographic analyses to investigations into group contracts and the impact of Unlimited Data Plans, you'll utilize various analytical techniques, including the SWITCH() function, to uncover key drivers of churn. Through the creation of a comprehensive overview report and detailed pages on age brackets, group contracts, payment methods, and contract types, you'll synthesize these insights, culminating in a thorough analysis encompassing data plans, charges, and state-specific characteristics. This case study provides a hands-on Power BI experience, offering practical insights into customer churn analysis and empowering Databel to refine its customer retention strategies.

Dashboard

Analyzing Customer Churn