cohort-analysis
Time-based cohort analysis with retention and behavior tracking. Use when analyzing user retention over time, comparing cohort performance, identifying lifecycle patterns, or measuring feature adoption by cohort.
When & Why to Use This Skill
This Claude skill enables advanced time-based cohort analysis to track user retention and behavior patterns with precision. By grouping users into cohorts based on shared characteristics or acquisition dates, it helps businesses identify lifecycle trends, compare segment performance, and measure the long-term impact of product changes or marketing strategies.
Use Cases
- SaaS Retention Tracking: Analyze monthly active users to pinpoint exactly when churn occurs in the customer lifecycle and develop targeted re-engagement strategies.
- Marketing ROI Analysis: Compare the long-term retention and value of users acquired through different channels, such as organic search versus paid advertising.
- Feature Adoption Measurement: Evaluate how specific product updates or new feature releases influence the engagement levels of new user cohorts over time.
- Revenue Pattern Identification: Track recurring revenue and purchase frequency across different customer groups to identify high-value segments and expansion opportunities.
| name | cohort-analysis |
|---|---|
| description | Time-based cohort analysis with retention and behavior tracking. Use when analyzing user retention over time, comparing cohort performance, identifying lifecycle patterns, or measuring feature adoption by cohort. |
Cohort Analysis
Quick Start
Analyze how groups of users/customers (cohorts) behave over time, typically measuring retention, revenue, or engagement patterns.
Context Requirements
- Dataset: User/customer event data
- Cohort Definition: How to group users (by signup month, acquisition channel, etc.)
- Retention Metric: What counts as "retained" (login, purchase, usage, etc.)
- Time Periods: Analysis granularity (daily, weekly, monthly)
Context Gathering
Initial Questions:
"Let's set up cohort analysis. I need:
What are we analyzing?
- User retention (returning users)
- Revenue retention (recurring purchases)
- Feature adoption (using specific features)
- Other behavior
How should we define cohorts?
- By signup date (most common)
- By acquisition channel
- By first purchase date
- By product/plan tier
- Other dimension
What counts as 'active' or 'retained'? Examples:
- Logged in at least once
- Made a purchase
- Used feature X
- Spent >10 minutes
What time periods?
- Daily cohorts (for apps with daily usage)
- Weekly cohorts
- Monthly cohorts (most common for SaaS)
- Quarterly cohorts"
For Dataset:
"I need data with:
- User ID (to track individuals)
- Cohort date (e.g., signup_date)
- Activity dates (e.g., login_date, purchase_date)
- Cohort attributes (optional: channel, plan, etc.)
Can you provide:
- File upload (CSV/Excel), OR
- Database query to fetch this, OR
- Description of tables and I'll write the query?"
Validation Questions:
"Before I proceed:
- What minimum cohort size should we analyze? (I recommend >100 users)
- How many periods should we track? (e.g., 12 months, 8 weeks)
- Any cohorts to exclude? (e.g., test users, employees)"