Can this skill help with long-term business goals?

Yes, it utilizes a metrics hierarchy that connects tactical operational data to high-level strategic North Star goals and lagging business indicators.

What is the a-b-test-design-pm skill?

It is a specialized Claude Code skill designed to help product managers create structured experimentation plans and define robust metrics frameworks for feature development and optimization.

How does this skill help avoid vanity metrics?

The skill includes specific anti-pattern mitigation that directs users toward quality and retention metrics, ensuring data represents real value rather than just high volume.

What documentation standards is this skill grounded in?

This skill is grounded in industry-standard frameworks including SWEBOK, AIPMM, and principles from Lean Analytics and Marty Cagan’s product methodology.

A/B Test Design for Product Managers

Name: A/B Test Design for Product Managers
Author: sethdford

bysethdford

•

분석 및 모니터링

Designs data-driven A/B tests and measurement frameworks to optimize product performance and user behavior through systematic experimentation.

The a-b-test-design-pm skill empowers product managers to move beyond intuition by providing a structured framework for experimentation and data analysis within Claude Code. It guides users through the process of defining metric hierarchies, identifying leading indicators versus lagging results, and establishing clear baselines for product features. By grounding metrics in strategic goals like North Star alignment, this skill ensures that experiments deliver actionable insights while providing guardrails against common pitfalls like vanity metrics or analysis paralysis.

주요 기능

015 GitHub stars

02Metric hierarchy definition (Strategic, Operational, and Diagnostic)

03Structured experiment plan generation with clear success criteria

04Identification of leading indicators for early signal detection

05Baseline and target setting for objective performance tracking

06Cohort analysis integration to monitor specific user group behavior

사용 사례

01Optimizing conversion funnels using cohort-based experimentation and review cadences

02Troubleshooting declining user engagement through diagnostic metric investigation

03Planning a new feature rollout with specific success thresholds and data collection methods

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sethdford/claude-skills a-b-test-design-pm

For use in Claude.ai and ChatGPT

주요 기능

015 GitHub stars

02Metric hierarchy definition (Strategic, Operational, and Diagnostic)

03Structured experiment plan generation with clear success criteria

04Identification of leading indicators for early signal detection

05Baseline and target setting for objective performance tracking

06Cohort analysis integration to monitor specific user group behavior

사용 사례

01Optimizing conversion funnels using cohort-based experimentation and review cadences

02Troubleshooting declining user engagement through diagnostic metric investigation

03Planning a new feature rollout with specific success thresholds and data collection methods

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sethdford/claude-skills a-b-test-design-pm

For use in Claude.ai and ChatGPT