Cohort Retention Analysis
Analyzes e-commerce retention curves and acquisition cohorts to diagnose customer health and optimize long-term value.
This skill transforms Claude into a specialized e-commerce retention analyst capable of deep-diving into cohort survival, LTV by channel, and revenue versus customer retention metrics. It leverages sophisticated frameworks like the 'Smile Curve' interpretation and 'Early-Warning Indicators' to identify decaying cohorts before they impact the bottom line. By separating channel-mix effects from product-engagement signals, it helps operators make data-driven decisions on acquisition spend and design rigorous intervention tests to improve repeat purchase behavior.
主な機能
01Structured framework for designing statistically sound intervention tests
02Multi-channel LTV analysis across 30, 90, 180, and 365-day windows
03Five-point early-warning dashboard for detecting cohort deterioration
043 GitHub stars
05Automated cohort survival curve generation and diagnostic interpretation
06Comparison of revenue retention versus customer retention metrics
ユースケース
01Diagnosing if recent acquisition cohorts are underperforming compared to historical benchmarks
02Comparing the long-term profitability of customers from Meta ads versus organic search
03Designing and pre-registering experiments to increase second-purchase rates