Cohort Analysis Interpreter

Free v1.0.0 2 views

Interpret SaaS cohort retention data with benchmark comparisons, trend analysis, and actionable recommendations to improve user retention.

What You Get

Transform confusing retention tables into clear insights about which user segments perform best, where users are churning, and what specific actions to take to improve retention rates.

The Problem

SaaS founders struggle to interpret cohort analysis results - they don't know if their retention is good or bad, which patterns matter, or what actions to take. Without frameworks for comparison and interpretation, they face analysis paralysis and miss opportunities to improve retention through targeted interventions.

The Solution

This skill applies a systematic interpretation framework to cohort retention data, comparing metrics against industry benchmarks, identifying critical drop-off points, analyzing cohort-to-cohort trends, and providing specific segmentation recommendations. It transforms raw retention numbers into actionable insights by explaining what patterns mean for the business and prioritizing improvements by impact. Users receive clear assessments (good/average/concerning), benchmark comparisons showing gaps, specific insights about activation and retention problems, and concrete action plans organized by timeframe.

How It Works

  1. 1 Validate data quality (cohort size, time range, completeness)
  2. 2 Extract product context (type, pricing, target segment, business model)
  3. 3 Compare retention metrics against industry benchmarks by product category
  4. 4 Analyze retention curve shape to identify patterns (cliff drops, steady erosion, stabilization)
  5. 5 Calculate critical metrics (first-period drop, stabilization rate, retention half-life)
  6. 6 Generate segmentation recommendations based on product type and observed patterns
  7. 7 Prioritize action recommendations by timeframe and impact
  8. 8 Format structured output with assessment, benchmarks, insights, and next steps

What You'll Need

  • Cohort retention data in table format showing retention rates over time periods
  • Product context: product type (B2B/B2C SaaS), pricing tier, target market
  • At least 4 time periods of data for meaningful trend analysis
  • Cohort sizes of 30+ users per cohort recommended for reliability

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