Agent skill · data analytics · yonatangross
product-analytics
A/B test evaluation, cohort retention, funnels and significance. Use when analyzing experiments, feature adoption or conversion drop-offs.
Why this skill is useful
Provides specific methodologies and SQL queries for cohort retention and funnel analysis that the AI wouldn't reliably generate on its own.
What it needs
About 4k tokens when loaded. Last updated 2026-08-06. 215 stars on the source repository.
What this skill does
Product Analytics Frameworks for turning raw product data into ship/extend/kill decisions. Covers A/B testing, cohort retention, funnel analysis, and the statistical foundations needed to make those decisions with confidence. Quick Reference Category Rules Impact When to Use ---------- ------- -------- ------------- A/B Test Evaluation 1 HIGH Comparing variants, measuring significance, shipping decisions Cohort Retention 1 HIGH Feature adoption curves, day-N retention, engagement scoring Funnel Analysis 1 HIGH Drop-off diagnosis, conversion optimization, stage mapping Statistical Foundations 1 HIGH p-value interpretation, sample sizing, confidence intervals Total: 4 rules across 4 categories A/B Test Evaluation Load rules/ab-test-evaluation.md for the full framework. Quick pattern: Decision rules: SHIP — p < 0.05, CI excludes zero, no guardrail regressions EXTEND — trending positive but underpowered (add runtime, not reanalysis) KILL — null result or guardrail degradation See rules/ab-test-evaluation.md for sample size formulas, SRM checks, and pitfall list. Cohort Retention Load rules/cohort-retention.md for full methodology. Quick pattern: Retention benchmarks (SaaS): Day 1: 40–60% is healthy Day 7: 20–35% is healthy Day 30: 10–20% is healthy Flat curve after day 30 = product-market fit signal See rules/cohort-retention.md for behavior-based cohorts, feature adoption curves, and engagement scoring. Funnel Analysis Load rules/funnel-analysis.md for full methodology. Quick pattern: Optimization order: Fix the largest drop-off first. A 5-point improvement at a high-volume step is worth more than a 20-point improvement at a low-volume step. See rules/funnel-analysis.md for segmented funnels, micro-conversion tracking, and prioritization patterns. Statistical Foundations Plain-English explanations of the stats every PM needs. Load references/stats-cheat-sheet.md for formulas and quick lookups. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills yonatangross/product-analytics