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