mcpbeat

Product Analytics

nicepkg/product-analytics

Measure what matters with proper event tracking, funnels, cohorts, and metrics. Use when setting up analytics, tracking features, or understanding behavior.

1k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
275
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/nicepkg/ai-workflow --skill product-analytics

The instruction itself

13 sections, as written by the author

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

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

How to use it

Copy the folder

Take nicepkg/product-analytics from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.