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cohort-analysis

Analyze user retention, feature adoption, and engagement trends across cohorts from CSV, Excel, or JSON data.

Updated Apr 8, 2026
Search Tags:#engagement#visualization#retention#cohort analysis#churn#product analytics#feature adoption
One-click install
npx skills add https://github.com/stefanomartiradonna/claude-skills --skill cohort-analysis-stefanomartiradonna
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cohort-analysis
Source: https://github.com/stefanomartiradonna/claude-skills/tree/main/pm-data-analytics-cohort-analysis
Command: npx skills add https://github.com/stefanomartiradonna/claude-skills --skill cohort-analysis-stefanomartiradonna

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Product teams often have raw engagement data but no structured way to turn it into retention insights. This Skill performs cohort analysis on user data, surfacing retention curves, churn patterns, and feature adoption trends, then recommends follow-up research to explain the numbers. ## Core Features & Use Cases - Retention Analysis: Calculate cohort retention rates, identify drop-off points, and compare cohort performance over time. - Visualizations: Generate retention heatmaps, cohort progression line charts, and feature adoption comparison charts. - Research Recommendations: Suggest targeted follow-ups such as churn interviews, usage surveys, session replays, and A/B tests. - Use Case: Upload a CSV of monthly signup cohorts with engagement scores and ask why Q4 cohorts underperform Q3 — receive retention curves, anomaly flags, and a prioritized research plan. ## Quick Start Upload your cohort data file and ask to analyze retention patterns and identify which cohorts show the strongest long-term engagement.

Frequently Asked Questions about cohort-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze user retention by cohort?▼

Provide data with a cohort identifier (such as signup month), time periods, and engagement metrics. The analysis calculates retention rates per cohort, plots retention curves, and flags drop-off points and anomalies across cohorts.

What data format do I need for cohort analysis?▼

CSV, Excel, or JSON files work, with columns for a cohort identifier, time period, user ID, and engagement metrics like feature usage or activity scores. At least 3-4 cohorts are recommended for meaningful pattern identification.

Can cohort analysis track feature adoption over time?▼

Yes. Include feature usage columns in your data and the analysis computes adoption rates per cohort, builds comparison charts, and identifies which cohorts adopted fastest and where adoption stalls.

Does cohort analysis explain why users churn?▼

Quantitative analysis shows where and when churn happens but not why. The output includes recommendations for qualitative follow-ups such as churned-user interviews, session replays, and win/loss analysis to uncover causes.

What are the limitations of cohort retention analysis?▼

Results depend on data quality: missing values, too few cohorts, or no time dimension limit insight depth. Small cohort sizes produce noisy retention curves, and correlation between cohorts and outcomes does not establish causation.

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