retention-analysis

Analyze user retention and churn patterns to identify drop-off points.

Updated Aug 23, 2026

Search Tags:#retention #user engagement #cohort analysis #churn #stickiness #product analytics

Ready to run

npx skills add https://github.com/TimothyNguyen04/pmos --skill retention-analysis-timothynguyen04

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: retention-analysis
Source: https://github.com/TimothyNguyen04/pmos/tree/main/PM-OS/.claude/skills/retention-analysis
Command: npx skills add https://github.com/TimothyNguyen04/pmos --skill retention-analysis-timothynguyen04

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you understand why users stay or leave your product, identify key drop-off points, and discover actionable strategies to improve user retention and product stickiness.

Core Features & Use Cases

Cohort Analysis: Analyze retention trends across different user groups over time.
Churn Diagnosis: Pinpoint the primary reasons users stop using your product.
Retention Strategy Development: Generate data-driven hypotheses and recommendations for improving user engagement and lifetime value.
Use Case: A SaaS company notices a significant drop in users after the first week. They use this Skill to analyze their D7 retention, compare the behavior of retained vs. churned users, and identify that users who don't complete the core setup within 5 minutes are most likely to churn, leading to an intervention focused on onboarding speed.

Quick Start

Analyze my product's retention data to identify key drop-off points and suggest improvements.

Frequently Asked Questions about retention-analysis

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

FAQPage Schema

How do I analyze user retention and identify key drop-off points?▼

Cohort analysis tracks user retention trends across different groups over time to pinpoint exactly when drop-offs occur. By comparing retained versus churned user behavior, you can identify primary churn drivers and develop data-driven strategies to improve product stickiness.

What is cohort analysis and how does it help reduce churn?▼

What's the best way to diagnose why users are churning from my SaaS product?▼

Churn diagnosis pinpoints the primary reasons users stop using your product by comparing retained versus churned user behavior. Identifying specific drop-off points, like incomplete onboarding within the first five minutes, allows you to target interventions and improve user stickiness.

Can I use product analytics data to improve user stickiness and engagement?▼

Product analytics data drives user stickiness by identifying behavioral differences between retained and churned cohorts. Analyzing this data uncovers friction points in the user journey, allowing you to generate targeted strategies that encourage long-term product adoption and reduce churn.

How do I generate data-driven retention strategies from churn analysis?▼

Generate data-driven retention strategies by diagnosing churn patterns and comparing retained versus churned user behavior to find key drop-off points. This analysis directly informs product development, yielding actionable interventions that boost user stickiness and lifetime value.