This project involved a deep dive into customer data to understand factors contributing to churn and to develop predictive models for early churn detection. The dashboards provide insights into customer segments, loyalty trends, and the impact of various customer engagement strategies.
The goal was to provide a robust analytical framework for businesses to proactively manage customer relationships and optimize retention strategies, ultimately increasing customer lifetime value (CLV). It demonstrates strong capabilities in data analysis and dashboarding for strategic business outcomes.
Technologies Used
- Power BI
- SQL
- Customer Data Platforms
Key Features
Cohort analysis for retention rates Churn prediction model insights Customer lifetime value (CLV) analysis Effectiveness of marketing campaigns on retention