Product Analytics

A solid foundation for product analytics that covers the essentials without overthinking it. You get event tracking patterns, funnel and cohort analysis templates, and a clear metrics hierarchy built around the North Star concept. The examples are practical, showing you exactly how companies like Slack and Spotify think about their key metrics. The retention curves and dashboard structures give you concrete benchmarks to aim for. It's more of a mental model and reference than deep implementation details, but that's honestly what you need when setting up analytics. The tool recommendations are standard but sensible. Good for getting alignment on what to measure before you start tracking everything and learning nothing.

skills.sh installs: 244
GitHub stars: 39
last updated: Aug 21, 2026

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Install

$ npx -y skills add daffy0208/ai-dev-standards --skill product-analytics --agent claude-code

Installs into .claude/skills of the current project.

Files

Product Analytics

Measure what matters and make data-driven decisions.

North Star Metric

The ONE metric that represents customer value

Examples:
  Slack: Weekly Active Users
  Airbnb: Nights Booked
  Spotify: Time Listening
  Shopify: GMV

Your North Star should: ✅ Represent customer value
  ✅ Correlate with revenue
  ✅ Be measurable frequently
  ✅ Rally the team

Key Metrics Hierarchy

North Star Metric
  ├── Input Metrics (drive North Star)
  │   ├── Acquisition
  │   ├── Activation
  │   └── Retention
  └── KPIs (business health)
      ├── Revenue
      ├── Churn
      └── LTV

Event Tracking

// Track user actions
analytics.track('Button Clicked', {
  button_name: 'signup',
  page: 'homepage',
  user_id: '123'
})

// Track page views
analytics.page('Homepage', {
  referrer: document.referrer,
  path: window.location.pathname
})

// Identify users
analytics.identify('user-123', {
  email: 'user@example.com',
  plan: 'pro',
  created_at: '2024-01-15'
})