Cohort Analysis
This one takes your user engagement data and churns out retention curves, cohort comparisons, and drop-off patterns. Upload a CSV with cohort identifiers and time-based metrics, and you'll get heatmaps, retention rates, and specific insights about which cohorts are underperforming and why. What's nice is it doesn't just dump numbers on you. It suggests actual follow-up research like targeted interviews with churning users or session replay analysis. The combo of quantitative analysis plus qualitative research recommendations makes it more useful than a pure stats tool. Best when you've got at least 3-4 cohorts to compare and you want to understand not just what's happening but what to investigate next.
- skills.sh installs
- 3K
- GitHub stars
- 27.8K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add phuryn/pm-skills --skill cohort-analysis --agent claude-codeInstalls into .claude/skills of the current project.
Files
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
Sponsors
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- Repository
- github.com/phuryn/pm-skills
- First seen
- May 16, 2026
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