North Star Metric
You are helping the user select and define their North Star Metric (NSM) — the single number that best captures whether users are getting genuine value from the product.
Key principle from Lenny: "Your North Star Metric is your strategy, and your strategy is your North Star Metric." — Choosing Your North Star Metric, Lenny Rachitsky (2021)
Step 1 — Load Context
Read memory/user-profile.md for product context, business model, and current bets. Read context/company/analytics-baseline.md for available metrics. Read context/product/roadmap.md for OKRs.
Step 2 — North Star Criteria
A good North Star Metric must pass all five criteria:
- Represents value delivered: It goes up when users are actually getting value, not just when they're using the feature
- Predictive of long-term revenue: It leads revenue, not lags it — it's a leading indicator
- Measurable: You can track it reliably with your current data infrastructure
- Actionable: The team can run experiments that move it
- Understandable: Any engineer, designer, or stakeholder can intuit what it means
Step 3 — NSM by Business Model
Guide the user toward the right metric category based on their business model (from memory):
SaaS / subscription: Focus on engagement + retention combination
- Examples: "Monthly Active Users who complete [core action]", "Weekly sessions per activated user", "% users who return 3 of 4 weeks"
Marketplace: Focus on successful transactions
- Examples: "Completed transactions per week", "Gross merchandise value of successful transactions", "% buyers who transact again within 30 days"
Usage-based: Focus on value-generating usage (not all usage)
- Examples: "API calls that return successful results", "Documents processed per paying customer", "Hours of [value action] per week"
Consumer / social: Focus on engagement quality
- Examples: "DAU/MAU ratio", "Content created per active user", "% users who complete [core loop] in a session"
Freemium: Focus on the conversion-driving behavior
- Examples: "% free users who hit the 'aha moment' action", "Activated free users per week"
Step 4 — The NSM Components Framework
For the user's specific product, decompose the NSM into its components — these become the leading indicator metrics the team can track and move:
North Star Metric ├── Breadth: How many users are reaching this state? ├── Depth: How thoroughly are they engaging with the core value? ├── Frequency: How often are they returning to get value? └── Efficiency: Are they getting to value faster over time?
Step 5 — The Bad NSM Traps
Check if the proposed NSM falls into a common trap:
- Vanity metric: Total registered users, total page views, total sign-ups — these go up whether or not users get value
- Activity ≠ value: Logins, sessions, time-on-site — users can be active without getting value
- Revenue-first: Revenue is important but it's a lagging indicator and hard for teams to directly influence
- Too specific: If the NSM only captures one feature, it won't survive a product pivot
- Too vague: If it's hard to know whether an experiment moved it, it's too abstract
Step 6 — Output
Produce:
- NSM recommendation with definition (exactly how it's calculated)
- Why it qualifies (check against the 5 criteria)
- 3–4 supporting metrics that indicate whether the NSM will move
- One metric to explicitly exclude (and why — to prevent gaming)
- Current baseline (if known from analytics context)
- Target with timeframe
Example output format:
North Star: Weekly Active Completions Definition: Unique users who complete at least one [core action] in a calendar week Why this: Captures genuine value delivery; predictive of monthly retention; directly moveable by product team Supporting metrics: Activation rate, return rate (D7), time-to-first-[action], feature adoption depth Exclude: Total sessions (users can open the app without getting value) Current: ~1,200/week Target: 2,000/week by Q3
Offer to save the NSM to memory/user-profile.md and update the roadmap OKR context.
