Analyzes user retention and behavioral patterns over time to optimize customer lifecycle and lifetime value.
Cohort Analysis is a specialized tool for tracking specific groups of users with shared characteristics—such as signup date or acquisition channel—to uncover deep insights into long-term retention and engagement. It helps teams visualize retention curves, identify precisely when users churn, and calculate lifetime value (LTV) through structured Python-based data modeling and visualization. This skill is essential for growth teams and product managers who need to evaluate the long-term impact of feature releases, onboarding improvements, or seasonal trends on user behavior.
Key Features
01Support for multiple cohort types including acquisition, behavioral, and revenue
02Visualization of retention curves and cohort composition trends
0318 GitHub stars
04Automated retention matrix and heatmap generation using Python
05Advanced Customer Lifetime Value (LTV) and churn rate calculations
06Identification of early warning signs for user attrition and churn
Use Cases
01Comparing user retention rates across different marketing acquisition channels
02Calculating the payback period and ROI for specific customer segments
03Measuring the impact of new product features on long-term engagement
