cohort-analysis
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
Install
git clone https://github.com/phuryn/pm-skills /tmp/pm-skills && ln -s /tmp/pm-skills/pm-data-analytics/skills/cohort-analysis ~/.claude/skills/cohort-analysisFrom 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.
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