cohort-analysis

From README

Cohort Analysis & Retention Explorer Purpose Analyze user engagement and retention patterns by cohort to identify trends in user behavior, feature adoption, and long-term engagement. Combine quantitative insights with qualitative research recommendations. How It Works Step 1: Read and Validate Your Data Accept CSV, Excel, or JSON data files with user cohort information Verify data structure: cohort identifier, time periods, engagement metrics Check for missing values and data quality issues Summarize key statistics (cohort sizes, date ranges, metrics available) Step 2: Generate Quantitative Analysis Calculate cohort retention rates and engagement trends Identify retention curves, drop-off patterns, and anomalies Compute feature adoption rates across cohorts Calculate month-over-month or period-over-period changes Generate Python analysis scripts using pandas and numpy if requested Step 3: Create Visualizations Generate retention heatmaps (cohorts vs.