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product-analytics

Define and track product metrics across lifecycle stages with Python scripts.

2|Updated Mar 13, 2026
Search Tags:#metrics#dashboard#retention#cohort analysis#kpi#product analytics
One-click install
npx skills add https://github.com/zhangzhang-111-i/claude-skills111 --skill product-analytics-zhangzhang-111-i
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: product-analytics
Source: https://github.com/zhangzhang-111-i/claude-skills111/tree/main/product-team/product-analytics
Command: npx skills add https://github.com/zhangzhang-111-i/claude-skills111 --skill product-analytics-zhangzhang-111-i

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps product teams define, track, and interpret key product metrics across all stages of the product lifecycle, enabling data-driven decision-making.

Core Features & Use Cases

  • Metric Frameworks: Select and apply frameworks like AARRR, North Star, or HEART.
  • KPI Definition: Define stage-appropriate Key Performance Indicators (KPIs).
  • Dashboard Design: Structure effective dashboards for different audiences.
  • Cohort & Retention Analysis: Analyze user behavior over time to understand adoption and churn.
  • Use Case: A product manager needs to understand why user retention has dropped. They can use this skill to define relevant KPIs, analyze cohort retention curves, and identify friction points in the user journey.

Quick Start

Use the product-analytics skill to define KPIs for a pre-PMF product stage.

Frequently Asked Questions about product-analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I define KPIs for different product lifecycle stages?▼

To define KPIs for different product stages, apply metric frameworks like AARRR, North Star, or HEART to establish stage-appropriate indicators for discovery, growth, or mature phases.

What is the best way to analyze cohort retention and identify user churn?▼

Cohort retention analysis tracks user behavior over time to understand adoption and churn. By analyzing retention curves, you can identify friction points in the user journey and diagnose retention drops.

How do I structure effective product dashboards for different audiences?▼

Dashboard design structures metrics for specific audiences by selecting relevant KPIs and visualizing feature adoption trends, ensuring stakeholders see tailored product insights.

Can I use Python scripts for product metrics calculations and feature adoption tracking?▼

Yes, this approach utilizes Python scripts to calculate product metrics and reference documents for guidance, enabling you to interpret feature adoption trends and track KPIs quantitatively.

When should I use the North Star framework versus AARRR for product analytics?▼

Use AARRR for comprehensive funnel metrics across acquisition to referral, while North Star focuses on a single core metric tied to product value. Choose based on whether you need broad lifecycle tracking or focused growth alignment.

Why has my user retention dropped and how do I find the friction points?▼

To find why user retention dropped, define relevant KPIs and analyze cohort retention curves. This process isolates specific user groups to identify friction points in the user journey.

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