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metrics-frameworks skill

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This skill helps you select and instrument metrics using North Star and AARRR, enabling actionable dashboards and clear success criteria.

npx playbooks add skill menkesu/awesome-pm-skills --skill metrics-frameworks

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---
name: metrics-frameworks
description: Defines right metrics using North Star framework, AARRR, and leading vs lagging indicators. Use when choosing metrics, instrumenting products, creating dashboards, or distinguishing vanity metrics from actionable ones.
---

# Metrics That Matter

## When This Skill Activates

Claude uses this skill when:
- Choosing which metrics to track
- Instrumenting product analytics
- Creating dashboards
- Defining success criteria

## Core Frameworks

### 1. North Star Metric

**Definition:**
> The ONE metric that best captures the core value you deliver to customers

**Good North Star:**
- Measures value delivery (not vanity)
- Leading indicator of revenue
- Captures product vision
- Actionable by team

**Examples:**
- Airbnb: Nights booked
- Facebook: Daily active users
- Slack: Messages sent
- Amplitude: Weekly learning users (in Spotify)

### 2. AARRR Framework

**Pirate Metrics:**
- **Acquisition:** How users find you
- **Activation:** First value experience
- **Retention:** Users coming back
- **Revenue:** Monetization
- **Referral:** Viral growth

---

## Action Templates

### Template: Metrics Dashboard

```markdown
# Metrics Dashboard: [Product/Feature]

## North Star Metric
**Metric:** [name]
**Current:** [value]
**Target:** [goal]
**Why this metric:** [captures core value]

## Supporting Metrics

### Acquisition
- Signups: [X per day]
- Channels: [breakdown]
- Cost per acquisition: [$X]

### Activation
- Activation rate: [X]%
- Time to first value: [X minutes]

### Retention
- Day 1: [X]%
- Day 7: [X]%
- Day 30: [X]%

### Revenue
- ARPU: [$X]
- LTV: [$X]
- Conversion rate: [X]%

### Referral
- K-factor: [X]
- Referral rate: [X]%

## Leading vs Lagging
**Leading (predict future):**
- [Metric that predicts outcome]

**Lagging (measure past):**
- [Metric that measures result]
```

---

## Quick Reference

### 📊 Metrics Checklist

**Choose Metrics:**
- [ ] North Star defined
- [ ] AARRR covered
- [ ] Leading indicators identified
- [ ] Vanity metrics avoided

**Implement:**
- [ ] Tracking instrumented
- [ ] Dashboard created
- [ ] Goals set
- [ ] Review cadence established

---

## Key Quotes

**Amplitude:**
> "The best metrics measure value delivery, not just activity."

**Sean Ellis:**
> "If you can't measure it, you can't improve it."

Overview

This skill defines the right product metrics using the North Star framework, AARRR (pirate metrics), and the distinction between leading and lagging indicators. It helps teams choose meaningful measures, avoid vanity metrics, and translate product strategy into instrumented dashboards and clear success criteria. Use it to align teams on what to track and why.

How this skill works

I guide you to pick a single North Star metric that captures core user value and then layer supporting AARRR metrics (Acquisition, Activation, Retention, Revenue, Referral). For each metric I recommend whether it is a leading or lagging indicator and provide concrete instrumentation and dashboard templates. I also surface which metrics are actionable versus vanity so teams can focus on signals that predict business outcomes.

When to use it

Launching a new product or feature and defining success criteria
Choosing which analytics to instrument before development
Designing dashboards for product, growth, or executive reviews
Prioritizing experiments and OKRs based on measurable impact
Auditing existing metrics to remove vanity measures and add leading indicators

Best practices

Define one North Star that maps directly to customer value and team action
Cover AARRR stages to avoid blind spots in the funnel
Identify 2–3 leading indicators that reliably predict your North Star
Instrument metrics before launch and validate data quality continuously
Set clear targets, review cadence, and owner for each metric

Example use cases

Product manager sets a North Star (e.g., weekly active users engaging with core feature) and builds a dashboard with acquisition and retention cohorts
Growth team runs experiments and monitors leading indicators (activation rate, time-to-first-value) to predict conversion uplift
Analytics engineer instruments events and maps them to AARRR metrics so dashboards reflect true user value
Executive dashboard summarizes North Star, top leading indicators, and revenue metrics for monthly reviews
Startup replaces vanity metrics (page views) with actionable metrics (time-to-first-success, repeat use rate) to prioritize roadmap

FAQ

How do I pick a North Star when multiple actions create value?

Choose the metric that best captures recurring, core value delivery and that the team can influence directly; supplement with supporting metrics for other value signals.

What counts as a leading indicator?

A leading indicator is a measurable behavior that changes before the North Star moves and is causally linked to it, like activation rate predicting retention.