Can I use this to identify why my metrics are failing?

Yes, the skill includes an anti-patterns check to identify issues like vanity metrics, lack of baselines, or measuring outcomes without leading indicators.

How does this help with user onboarding?

The skill defines a Setup-Aha-Habit funnel, helping you identify specific thresholds and time-to-value targets to ensure users reach the core value of your product quickly.

Does it provide engagement segmentation?

Yes, it provides default definitions for Casual, Core, and Power users based on session frequency and engagement depth.

What metrics hierarchies does this skill support?

It supports multiple frameworks including Outcome-Intermediate-Leading, North Star-L1-L2, and Business-Product-Feature hierarchies to align with your team's preference.

What are tradeoff metrics in this context?

Tradeoff metrics are safeguard indicators that ensure optimizing one metric (like adoption) doesn't cause a decline in another (like user quality or tech debt).

Product Metrics Design

Name: Product Metrics Design
Author: abhitsian

byabhitsian

0•

분석 및 모니터링

Designs comprehensive metrics frameworks with outcome-driven hierarchies, activation funnels, and engagement dimensions for product success.

The Metrics Design skill provides a structured methodology for Product Managers and developers to define how product success is measured. It moves beyond vanity metrics by implementing proven frameworks like the Outcome-Intermediate-Leading hierarchy or the North Star model. Users can define clear activation funnels—identifying the Setup, Aha, and Habit moments—while monitoring engagement through breadth, depth, and intensity. The skill also proactively identifies tradeoff metrics and anti-patterns to ensure that optimizations in one area don't negatively impact the broader product ecosystem.

주요 기능

01Hierarchical metrics modeling (Outcome, Intermediate, and Leading indicators)

02Activation funnel mapping (Setup, Aha moment, and Habit formation)

03User segmentation frameworks based on behavior and session frequency

04Multi-dimensional engagement tracking across breadth, depth, and intensity

050 GitHub stars

06Tradeoff and counter-metric identification to prevent optimization bias

사용 사례

01Defining the North Star metric and supporting L1/L2 drivers for a new feature launch

02Establishing 'Aha moment' thresholds to improve user onboarding and retention

03Auditing existing analytics to replace vanity metrics with actionable leading indicators

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add abhitsian/compound-pm-marketplace metrics-design

For use in Claude.ai and ChatGPT

Download Skill