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cohort-analysis

Analyze cohort retention data to highlight engagement and churn patterns.

2|Updated Apr 9, 2026
Search Tags:#visualization#retention#cohort-analysis#user-behavior#data-validation#feature-adoption#research-recommendations
One-click install
npx skills add https://github.com/skytiger6724/qwen-skills --skill cohort-analysis-skytiger6724
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cohort-analysis
Source: https://github.com/skytiger6724/qwen-skills/tree/main/cohort-analysis
Command: npx skills add https://github.com/skytiger6724/qwen-skills --skill cohort-analysis-skytiger6724

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill removes the guesswork from understanding cohort performance by turning messy engagement data into clear retention, adoption, and churn findings that guide product decisions.

Core Features & Use Cases

  • Data validation and summary: Accept CSV, Excel, or JSON inputs, verify cohort structures, and report data quality so analysis starts on solid footing.
  • Quantitative analysis and scripts: Compute retention curves, adoption rates, anomalies, and optionally generate reusable Python scripts for ongoing tracking.
  • Visualizations and research planning: Produce heatmaps, line charts, and comparison views while suggesting targeted follow-up interviews or experiments to probe surprising trends.

Quick Start

Upload your cohort dataset, specify the relevant time periods, and ask for retention and adoption insights.

Frequently Asked Questions about cohort-analysis

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

FAQPage Schema
How do I analyze cohort retention data to identify user churn patterns?▼

Cohort retention analysis validates dataset structures, calculates retention curves, and generates visualizations like heatmaps to highlight engagement drops and user churn patterns over specified time periods.

What is the best way to visualize feature adoption rates across monthly signup cohorts?▼

Visualizing feature adoption across monthly signup cohorts is best achieved by generating line charts and heatmaps that compare adoption rates over time, helping track engagement trends and spot anomalies.

Can I use CSV and Excel files for cohort analysis and data validation?▼

Yes, cohort analysis supports CSV, Excel, and JSON file inputs, automatically verifying cohort structures and reporting data quality to ensure your retention and adoption analysis starts on solid footing.

How do I generate reusable Python scripts for tracking user retention curves?▼

Generating reusable Python scripts for tracking user retention curves requires computing engagement metrics and adoption rates from validated cohort datasets, enabling ongoing tracking without manual recalculation.

Does cohort analysis provide follow-up research recommendations for drop-off investigations?▼

Yes, cohort analysis provides follow-up research recommendations by suggesting targeted interviews or experiments to probe surprising trends and anomalies discovered during user segmentation and drop-off investigations.

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