Following your customers through their journey (and why cohorts aren't enough)
Original: Customer State — a key building block of advanced customer analytics
Paul Levchuk
May 29, 2025
5 min read
Framework
Intermediate
Summary
How to group customers and users based on their behavioral patterns, including click-stream data, purchase history, feature usage, and session frequency. Covers RFM (Recency, Frequency, Monetary) analysis and customer lifecycle stage clustering.
Who This Is For
Marketing Analysts
Product Analysts
Growth Marketers
Key Takeaways
- Track customers across three time periods (previous, current, next month) to understand their complete behavioral trajectory
- New customers typically represent 60%+ of monthly revenue but have lower retention than existing active users
- Active customers (those who purchased within 30 days) show 3x higher retention rates than new or dormant customers
- Replace traditional cohort analysis with customer state segmentation that accounts for past purchase behavior
- Use percentage-based analysis instead of absolute figures to account for month-to-month business variations
Tools & Technologies
Customer purchase databases Data analysis tools (Excel, SQL, or similar) Customer analytics platforms
Topics Covered
customer-segmentation user-behavior rfm-analysis lifecycle-stages
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