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product-analytics

product-analytics

github.com/daffy0208Data & databases38241 installsUpdated 44w ago
Repository

About product-analytics

A product analytics skill for teams choosing metrics and interpreting user behavior. It covers North Star metrics, event tracking, funnels, cohorts, retention, and dashboards.

Key features

  1. 01North Star metric and KPI hierarchy
  2. 02Event tracking guidance
  3. 03Funnel and cohort analysis
  4. 04Retention metrics and curves
  5. 05Dashboard planning

Use cases

  1. 01Choose a customer-value metric
  2. 02Review signup funnel drop-off
  3. 03Compare retention across cohorts

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/daffy0208/ai-dev-standards --skill product-analytics

After installing, type/product-analyticsin Claude Code to confirm it loaded.

Bundled filesmanifest.yaml

Details

From the project README

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: '[email protected]',
  plan: 'pro',
  created_at: '2024-01-15'
})

Funnel Analysis

Sign-up Funnel:
  1. Land on homepage: 10,000 (100%)
  2. Click signup: 2,000 (20%)
  3. Fill form: 1,000 (10%)
  4. Verify email: 800 (8%)
  5. Complete onboarding: 400 (4%)

Insights:
  - Biggest drop: Homepage to signup (80% lost)
  - Fix: Clarify value prop, add social proof

Cohort Analysis

Week 1 Cohort (Jan 1-7):
  - D1: 80% active
  - D7: 40% active
  - D30: 20% active

Week 2 Cohort (Jan 8-14):
  - D1: 85% active (+5%)
  - D7: 50% active (+10%)
  - D30: 30% active (+10%)

Insight: Onboarding changes improved retention!

Retention Curves

Good Retention:
  - D1: 60-80%
  - D7: 40-60%
  - D30: 30-50%
  - Flattening curve (good!)

Bad Retention:
  - D1: 40%
  - D7: 10%
  - D30: 2%
  - Steep drop-off (bad!)

Key Metrics to Track

Acquisition
  • Traffic sources (organic, paid, referral)
  • Cost per click (CPC)
  • Conversion rate (visitor → signup)
Activation
  • Signup → first core action
  • Time to value
  • Onboarding completion rate
Retention
  • DAU / MAU (stickiness)
  • Retention rate D1, D7, D30
  • Churn rate
Revenue
  • MRR / ARR
  • ARPU (Average Revenue Per User)
  • LTV (Lifetime Value)
  • LTV:CAC ratio
Referral
  • Viral coefficient
  • Referral signups
  • NPS (Net Promoter Score)

## Tools

```yaml
Event Tracking:
  - Mixpanel (best for products)
  - Amplitude (good alternative)
  - PostHog (open-source)

Session Recording:
  - FullStory
  - LogRocket
  - Hotjar

A/B Testing:
  - Optimizely
  - VWO
  - Google Optimize (free)

Dashboard Design

Executive Dashboard:
  - North Star Metric (big number)
  - Revenue (MRR/ARR)
  - Key metric trends (graphs)

Product Dashboard:
  - Active users (DAU/WAU/MAU)
  - Feature usage
  - Retention cohorts
  - Funnels

Marketing Dashboard:
  - Traffic sources
  - Conversion rates
  - Cost per acquisition
  - ROI by channel

Summary

Great analytics:

  • ✅ One North Star Metric
  • ✅ Track everything
  • ✅ Regular review (weekly)
  • ✅ Share insights widely
  • ✅ Act on data quickly

Comments

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