Analysis / Analyst

Cohort Analysis Planner

Design cohort analysis frameworks for measuring user retention, engagement patterns, and lifecycle behavior over time.

ChatGPT, Claude · 0 copies · 0 views

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Product Type *What kind of product? (e.g., SaaS app, mobile game, e-commerce platform)

Retention Metric *What does 'retention' mean for your product? (e.g., login, purchase, active session)

Cohort Definition *How should users be grouped? (e.g., by signup week, first purchase month)

Time Period *How far back to analyze and how far forward to track (e.g., 12 months, 90-day retention window)

Rendered Prompt

You are a data analyst specializing in user behavior and retention analysis. Design a cohort analysis plan for {{product_type}} to analyze {{retention_metric}}.

Create a comprehensive cohort analysis framework with:

1. **Cohort Definition**: Define {{cohort_definition}} with:
   - Cohort grouping criteria (signup date, first purchase, first login, etc.)
   - Minimum cohort size for statistical validity
   - Exclusion criteria (test accounts, bots, etc.)

2. **Retention Metric**: Define {{retention_metric}} with:
   - Exact metric calculation method
   - Time periods to analyze (Day 1, Day 7, Day 30, Day 90)
   - Benchmarks and target retention curves

3. **Analysis Structure**: Outline the analysis approach:
   - Cohort retention table format
   - Visualization types (heatmaps, retention curves, stacked charts)
   - Segmentation dimensions (plan type, acquisition channel, geography)

4. **Time Period**: Specify {{time_period}} and:
   - Historical data requirements
   - Analysis windows and lookback periods
   - Update frequency recommendation

5. **Insights Framework**: Define what to look for:
   - Retention curve patterns (drop-off points, stabilization)
   - Churn indicators and leading signals
   - Improvement opportunity identification

6. **Actionable Outputs**: Structure for recommendations:
   - Target cohort interventions
   - Product improvement priorities
   - Marketing and engagement strategies

7. **Technical Requirements**: Data tables, tools, and SQL patterns needed.

Ensure the analysis plan is designed to produce actionable insights for improving user retention.

How to use

Describe your product type, the retention metric you care about, how you want to define cohorts, and the time period to analyze. This produces a complete analysis plan including SQL patterns and visualization specifications.

Example output

A cohort analysis plan with monthly cohorts defined by signup date, measuring retention as weekly active users making at least 1 project update. Includes a retention table template for 12 monthly cohorts across 12 weeks, segmentation by plan type and team size, and SQL patterns for calculating retention rates.

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