Define North Star

Define North Star Metric

When to use: During strategy planning, when metrics feel scattered, or when teams are optimizing different things

Framework source: Aakash Gupta's "Do you really need a North Star Metric?"

Quick Start

1. Tell me: "Help me define our North Star metric" (or "Validate our current North Star")
2. I will check context-library/business-info-template.md and context-library/strategy/ for your business model, growth stage, and existing metrics
3. I will ask about your core value, retention drivers, and business model to narrow candidates
4. We work through: Core Value identification, Metric formula (Frequency x Core Action x Breadth), Validation tests, Input metrics, and Guardrails
5. Output goes to outputs/analyses/north-star-[quarter].md

Key decision: Not every product needs a single North Star. Marketplaces, multi-product companies, and complex B2B may need a constellation of 2-4 metrics instead. I will help you decide which approach fits.

Context Routing Logic (Internal - for Claude)

Automatic Context Checks: When this skill is invoked, immediately check:

Context Priority:

1. Business model and revenue drivers FIRST
2. Current product stage and growth focus SECOND
3. Historical metrics data THIRD
4. Stakeholder expectations FOURTH

Cross-Skill Links:

• If building strategy → Link to /write-prod-strategy which uses North Star
• If defining feature metrics → Link to /feature-metrics which should ladder to North Star
• If analyzing retention → Link to /retention-analysis to identify leading indicators
• If setting up metrics framework → Link to /metrics-framework

Step 0: Understanding Your Current Metric State

Before defining your North Star, let me understand where you are...

Checking:

• context-library/business-info-template.md for your business model
• context-library/strategy/ for strategic direction
• context-library/metrics/ for baseline metrics and trends
• context-library/meetings/ for stakeholder priorities

Based on what I find, I'll show you:

Current Metric State

Business Model:

• [How do you make money? Subscription / marketplace / ads / transactions?]
• [Growth stage: acquisition focus / retention focus / monetization focus?]
• [TAM: addressable market size]

Existing Metrics:

• [Current metrics dashboard: what are you tracking?]
• [Metric trends: what's moving, what's flat?]
• [Stakeholder focus: what does leadership care about?]

Metric Gaps:

• [Metrics that aren't connecting to decisions: vanity metrics?]
• [Decisions being made without data: where are you flying blind?]

PM-Specific Diagnosis Questions

1. Business Model Clarity: Are you clear on what drives revenue/value in your business?
2. Growth Focus: Are you optimizing for growth, engagement, retention, or monetization?
3. Team Alignment: Do all teams agree on what success looks like?
4. Data Quality: Do you trust your existing metrics data?
5. Decision Speed: How quickly do you need to make decisions? (Hourly, daily, weekly, monthly?)

What is a North Star Metric?

Definition: The single metric that best captures the core value your product delivers to customers.

Do You Actually Need One?

When a North Star Metric Works Well:

✅ Product-led growth (PLG) companies

• Self-serve product
• Clear activation moment
• Example: Slack's "Teams sending 2,000+ messages"

✅ Consumer products with network effects

• Value increases with usage
• Example: Facebook's "Daily Active Users"

✅ Early-stage companies (Seed to Series B)

• Need focus and alignment
• Limited resources require prioritization

When a North Star Can Be Misleading:

❌ Marketplace/multi-sided platforms

• Optimizing for buyers might hurt sellers
• Need balanced metrics for both sides
• Example: Airbnb tracks host AND guest metrics

❌ Complex B2B enterprise products

• Multiple stakeholders with different needs
• Example: Salesforce has different success metrics by user role

❌ Companies with multiple business models

• Each line of business may need different metrics
• Example: Amazon (retail vs AWS vs ads)

The North Star Framework

A good North Star Metric has three components:

1. Core Action

What is the one thing users do that indicates they're getting value?

Examples:

• Spotify: Time spent listening
• Airbnb: Nights booked
• Slack: Messages sent
• LinkedIn: Weekly active users
• Notion: Documents created

2. Frequency

How often should this action happen to indicate real value?

Examples:

• Daily: Social apps (Instagram, TikTok)
• Weekly: Productivity tools (Notion, Figma)
• Monthly: Marketplace (Airbnb, Uber)
• Per-session: E-commerce (Amazon)

3. Breadth

Who needs to do this action for it to count?

Examples:

• Individual users: Netflix (hours watched per user)
• Teams: Slack (active teams sending messages)
• Multi-sided: Uber (completed trips)

Formula: [Frequency] × [Core Action] × [Breadth]

Examples:

Slack:

• Frequency: Daily
• Core Action: Messages sent
• Breadth: Active teams
• North Star: Daily Active Teams sending 2,000+ messages

Airbnb:

• Frequency: Per transaction
• Core Action: Nights booked
• Breadth: Guests
• North Star: Nights booked

Spotify:

• Frequency: Weekly
• Core Action: Time listening
• Breadth: Active users
• North Star: Weekly Active Users × Hours listened

How to Find Your North Star

Step 1: Identify Your Core Value

Answer these questions:

1. What problem does your product solve?

   • Not features, but the actual problem

2. When do users say "aha, this is valuable"?

   • Look at retention data: what do retained users do differently?

3. What action most correlates with retention?

   • Run cohort analysis
   • Compare churned vs retained users

Use this prompt:

Use /define-north-star and reference context-library/business-info-template.md

Help me identify our core value:
- Product: [describe your product]
- Customer problem: [what problem you solve]
- Retention data: [describe retained vs churned user behavior]

What action best captures when users get value?

Step 2: Validate Against Criteria

Your North Star should be:

✅ Measurable

• Can you track it accurately?
• Do you have the data infrastructure?

✅ Actionable

• Can teams influence it with their work?
• Are there levers to pull?

✅ Leading indicator

• Does it predict revenue/retention?
• Or is it just a vanity metric?

✅ Understandable

• Can everyone in the company explain it?
• Does it pass the "grandma test"?

✅ Captures sustainable value

• Not gameable
• Reflects real customer value

Step 3: Test for Tradeoffs

The real test: Does it help you make hard decisions?

Example decision scenarios:

Scenario 1: You can either:

• A) Improve conversion rate +10% (more signups)
• B) Improve Day 7 retention +5% (better activation)

Which moves your North Star more?

Scenario 2: Marketing wants to:

• Run a campaign that brings 10K new users (low quality)
• Or 1K highly-targeted users (high quality)

Which aligns with your North Star?

If your North Star doesn't help you choose, it's not working.

Common North Star Metrics by Category

Social / Community Products

• Facebook: Daily Active Users (DAU)
• Instagram: Daily Active Users sharing stories
• TikTok: Time spent watching videos
• Discord: Weekly Active Servers

Productivity / Collaboration

• Slack: Daily Active Teams (2,000+ messages)
• Notion: Weekly Active Users creating docs
• Figma: Weekly Active Designers
• Asana: Tasks completed per week

Marketplace / Transaction

• Airbnb: Nights booked
• Uber: Completed trips
• Etsy: Gross Merchandise Value (GMV)
• DoorDash: Orders completed

Media / Content

• Netflix: Hours watched per member
• Spotify: Hours listened per subscriber
• Medium: Time reading articles
• YouTube: Watch time

SaaS / B2B

• Salesforce: Active users per account
• HubSpot: Weekly active contacts managed
• Stripe: Payment volume processed
• Dropbox: Active files shared

Red Flags: Bad North Star Metrics

❌ Revenue as North Star

Problem: Revenue is an outcome, not a value metric

• Doesn't tell you WHY customers pay
• Can go up even if product value decreases (price increases)
• Lagging indicator (slow to respond)

Exception: Marketplaces where GMV = value delivered

❌ Number of Features Used

Problem: More features ≠ more value

• Can be gamed by adding trivial features
• Doesn't capture depth of value

Better: Usage of core feature

❌ Vanity Metrics (Signups, Downloads, Page Views)

Problem: No correlation to actual value or retention

• Can grow while business dies
• Doesn't reflect customer success

Better: Activation rate, active users

From North Star to Execution

Once you have your North Star, break it down into input metrics:

Example: Airbnb's "Nights Booked"

Input Metrics (things that drive Nights Booked):

1. Supply side:

   • Active listings
   • Listing quality score
   • Host responsiveness

2. Demand side:

   • Search-to-booking conversion
   • Repeat booking rate
   • Average trip length

3. Trust & safety:

   • Review ratings
   • Dispute rate
   • Insurance claims

Each team owns input metrics that ladder up to North Star.

How Teams Use the North Star

Product Team:

"Will this feature increase Nights Booked?"

• If yes → prioritize
• If no → deprioritize

Marketing Team:

"Will this campaign bring users who book nights?"

• Focus on qualified traffic, not just signups

Engineering Team:

"Will improving performance increase Nights Booked?"

• Faster search → more bookings → prioritize

Customer Success:

"Are our customers booking nights regularly?"

• If not, something's wrong with value delivery

Evolving Your North Star

Your North Star should evolve as your company matures:

Early stage (0-100K users):

• Focus: Activation and retention
• North Star: Weekly Active Users

Growth stage (100K-1M users):

• Focus: Sustainable growth loops
• North Star: Weekly Active Users engaging with core feature

Scale stage (1M+ users):

• Focus: Monetization and expansion
• North Star: Revenue per active user OR engagement + monetization hybrid

Enterprise stage:

• Multiple North Stars for different business units

Real-World Example: Slack

Slack's North Star Evolution:

2014-2015 (Early):

• North Star: Teams sending 2,000+ messages
• Why: Indicated real team adoption

2016-2018 (Growth):

• North Star: Daily Active Teams (2,000+ messages)
• Why: Added frequency dimension

2019-2021 (Scale):

• North Star: Weekly Active Users + Messages sent
• Why: Balance growth with engagement

2022+ (Enterprise):

• North Star: Active paid seats
• Why: Focus on monetization at scale

Key insight: North Star evolved with company stage

Worksheet: Define Your North Star

1. Core Value

What problem do you solve? ___________

2. Core Action

What do users do when they get value? ___________

3. Retention Correlation

What action correlates most with retention? ___________

4. Frequency

How often should users do this action? ___________

5. Breadth

Who needs to do this? (Individual, team, transaction) ___________

6. North Star Candidate

Formula: [Frequency] × [Core Action] × [Breadth]

7. Validation Checks

• Measurable? (Can we track it?)
• Actionable? (Can teams influence it?)
• Leading indicator? (Predicts retention/revenue?)
• Understandable? (Everyone gets it?)
• Sustainable? (Reflects real value?)

8. Tradeoff Test

Describe 2-3 hard decisions your North Star should help you make:

Alternative: Constellation of Metrics

If a single North Star doesn't work for you, use a constellation:

Example: Amazon

• Customer satisfaction (NPS)
• Selection (# of products)
• Price (value for money)
• Convenience (delivery speed)

Rule: No more than 4 metrics in your constellation

• More than 4 = unfocused strategy

Guardrail Metric Guidance

Every North Star needs 2-3 guardrail metrics to prevent destructive optimization.

Without guardrails, teams will find ways to game the North Star that hurt the business. The question to ask: "If we aggressively optimized [North Star], what could go wrong? That is your guardrail."

Common guardrail patterns:

1. Quality metric (e.g., NPS, CSAT, support ticket volume) -- Prevents growth at the expense of user satisfaction. Example: If North Star is "Weekly Active Users," a guardrail of "NPS stays above 40" prevents acquiring low-quality users who churn immediately.

2. Revenue/monetization metric (e.g., ARPU, conversion rate, LTV) -- Prevents engagement optimization that does not generate revenue. Example: If North Star is "time spent in app," a guardrail of "ARPU stays above $12/mo" prevents building addictive features that do not convert to paid.

3. Efficiency metric (e.g., CAC, cost per transaction, infrastructure cost per user) -- Prevents growth that is not sustainable. Example: If North Star is "completed transactions," a guardrail of "CAC stays below $50" prevents buying growth that does not pay back.

How to define guardrails:

• Set a minimum threshold (floor), not a target. Guardrails are "do not go below X," not "try to reach Y."
• Define what happens if breached: who gets alerted, what investigation to run, and what corrective action to take.
• Review guardrails quarterly. As the product matures, guardrail thresholds may need adjustment.

Output Template

North Star Metric Analysis: [Company Name]

Recommended North Star: [Metric Name] Formula: [How it is calculated] Current Value: [Baseline] Target: [Goal + timeline]

Validation

• Core Value Test: [Pass/Fail + reasoning]
• Leading Indicator Test: [Pass/Fail + reasoning]
• Tradeoff Test: [Pass/Fail + reasoning]

Input Metrics (Driver Tree)

Guardrail Metrics

Recommendation

[2-3 sentences on whether to adopt/keep/change the North Star, with timeline for review. Example: "Adopt Weekly Active Teams as your North Star for the next 6 months. Review at the end of Q3 to determine if the metric still reflects core value delivery as you move into enterprise. Schedule a North Star review meeting for September."]

Common Mistakes

❌ Changing your North Star every quarter

• Causes whiplash across teams
• Choose one and stick with it for 6-12 months

❌ Having different North Stars by team

• Defeats the purpose of alignment
• Everyone should rally around one metric

❌ Making it too complex

• If it requires a 10-minute explanation, it's too complex
• Should fit in one sentence

❌ Ignoring guardrails

• Optimize for North Star, but don't break the product
• Always have 3-5 guardrail metrics

Output Integration

Where Files Go

North Star definition:

• Active work: outputs/analyses/north-star-[quarter].md (your working definition)
• When finalized: Move to context-library/metrics/north-star-[year].md for reference
• Share widely: This becomes the basis for all team metrics

Link to Other Work

After defining North Star:

• Reference in strategy - "Our North Star metric is [X]" in /write-prod-strategy
• Guide PRDs - All feature PRDs should explain how they support North Star
• Inform roadmap - Roadmap priorities are evaluated by North Star impact
• Dashboard anchor - North Star sits at top of your metrics dashboard

Cross-Skill Integration

Feeds into:

• /write-prod-strategy - North Star becomes the Objective component
• /metrics-framework - North Star is your lagging metric anchor
• /feature-metrics - Feature success metrics should ladder to North Star
• /status-update - Progress toward North Star is tracked in updates

Pulls from:

• context-library/business-info-template.md - Business model informs what matters
• context-library/metrics/ - Historical data validates metric choices
• /retention-analysis - Understand what drives long-term success
• /activation-analysis - Early indicators of North Star movement

Related Skills

• /activation-analysis - Find your activation metric
• /feature-metrics - Choose experiment metrics that ladder to North Star
• /metrics-framework - Understand leading vs lagging metrics
• /retention-analysis - Measure what drives retention and North Star
• /write-prod-strategy - Connect North Star to strategy

Output Quality Self-Check

Before delivering the North Star analysis, verify:

• Metric is one sentence: The North Star can be stated in a single clear sentence (e.g., "Weekly Active Teams sending 2,000+ messages"). If it needs a paragraph to explain, it is too complex.
• Formula is explicit: The calculation is defined precisely enough that an analyst could implement it in SQL. No ambiguity about what counts and what does not.
• Baseline and target are included: Current value and target value with timeline are both specified. "Improve engagement" is not a North Star.
• Three validation tests passed: Core Value Test, Leading Indicator Test, and Tradeoff Test are each explicitly addressed with pass/fail and reasoning.
• Input metrics defined: At least 3 input metrics are identified with owners, showing how teams can influence the North Star.
• Guardrails defined: 2-3 guardrail metrics are specified with thresholds and breach actions. A North Star without guardrails is dangerous.
• Tradeoff scenario tested: At least one real decision scenario is described where the North Star helps choose between two options. If it does not help decide, it is not working.
• Review timeline set: A specific date to revisit the North Star is recommended (typically 6-12 months).

Framework credit: Adapted from Aakash Gupta's North Star Metric framework. Read the full article: https://www.news.aakashg.com/p/do-you-really-need-a-north-star-metric