retention-analysis
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
npx skills add majiayu000/claude-skill-registry --skill retention-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Retention Analysis Skill Analyze user retention patterns, predict customer churn, and optimize retention strategies using advanced statistical methods and machine learning techniques. ## Quick Start This skill helps you: 1. **Calculate retention rates** and churn metrics 2. **Build survival curves** using Kaplan-Meier analysis 3. **Perform cohort analysis** to understand behavior patterns 4. **Predict churn risk** with machine learning models 5. **Identify retention drivers** using Cox regression 6. **Generate actionable insights** for retention improvement ## When to Use - **SaaS Product Analysis**: User subscription renewal and cancellation patterns - **Membership Programs**: Member engagement and loyalty analysis - **E-commerce**: Customer repeat purchase behavior and subscription boxes - **Gaming Apps**: Player retention and engagement metrics - **Service Industries**: Customer satisfaction and long-term relationships - **Subscription Businesses**: Monthly/yearly subscription analysis ## Key Requirements Install required packages: ```bash pip install pandas numpy matplotlib seaborn scikit-learn lifelines ``` ## Core Workflow ### 1. Data Preparation Your data should include: -
- Quick Start
- When to Use
- Key Requirements
- Core Workflow
- 1. Data Preparation
- 2. Analysis Process
- 3. Output Deliverables
- Example Usage Scenarios
- SaaS Subscription Analysis
- Membership Program Analysis
- E-commerce Customer Retention
- Key Analysis Methods
- Survival Analysis
- Cohort Analysis
pip install pandas numpy matplotlib seaborn scikit-learn lifelines
What does the retention-analysis skill do?
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill retention-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.