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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

1. Dataset: User/customer event data
2. Cohort Definition: How to group users (by signup month, acquisition channel, etc.)
3. Retention Metric: What counts as "retained" (login, purchase, usage, etc.)
4. Time Periods: Analysis granularity (daily, weekly, monthly)

Context Gathering

Initial Questions:

"Let's set up cohort analysis. I need:

1. What are we analyzing?

   • User retention (returning users)
   • Revenue retention (recurring purchases)
   • Feature adoption (using specific features)
   • Other behavior

2. How should we define cohorts?

   • By signup date (most common)
   • By acquisition channel
   • By first purchase date
   • By product/plan tier
   • Other dimension

3. What counts as 'active' or 'retained'? Examples:

   • Logged in at least once
   • Made a purchase
   • Used feature X
   • Spent >10 minutes

4. 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)"

Workflow

1. Data Preparation