North star metric
The single metric a company commits to as the leading indicator of long-term value delivered to customers. Marketing experiments either move it, leave it, or hurt it — every result reads against that one number.
A north star metric is the one number a team agrees captures the value the product creates for users. It is leading (it predicts revenue, not just records it), measurable in the short term, and durable enough that it stays meaningful for years. Spotify is north star is hours listened. Airbnb is is nights booked. Slack is messages sent in a single team. The shape of the metric reveals what the company believes growth actually means.
For an experiment program, the north star is the gravitational center. Every test either moves it, is neutral against it, or pulls against it — and the verdict has to read against that fact. A 20% lift in signups that does not move the north star is not necessarily a win; it might just be acquiring people who never deliver value. Pre-committing the north star in the experiment contract turns "did this work" into a real question with a real answer instead of a meeting about which dashboard slice to celebrate.
When to use it
Pick a north star early — the first 10 to 50 customers is enough signal to know what value looks like. Re-anchor every experiment contract to the same metric so wins and losses are comparable across surfaces and quarters.
What this looks like in practice
A good north star metric has three properties. First, it is leading: it moves before revenue moves, so you can see the verdict on a test in weeks instead of years. Second, it is countable in the moment, not just in retrospect: you can decide "did the test move it" without quarterly reporting infrastructure. Third, it is meaningful to the customer: it is a thing they would be sad to lose if it stopped working, not a vanity number that only the marketing team cares about.
The north star is the one metric you commit to even when other metrics rebel against it. A team aiming for "weekly active workspaces" will sometimes ship changes that drop signup conversion. That is fine — signup is a means, the active workspace is the end. Without that hierarchy, every test becomes a debate between competing dashboards. With it, the conversation is shorter and the verdict is sharper: did this move the one number we picked.
North star metrics drift. Spotify is north star started as paid subscribers, then evolved to time spent, then to specific listening behaviors. That is not a failure of the framework — it is the framework working. Re-evaluate the north star annually, not weekly. Quarterly redefinition is just having no north star at all dressed up in different language each season.
A worked example
A B2B SaaS picks "weekly active workspaces with at least three connected integrations" as the north star — it is a leading indicator of paid retention and uniquely measurable. A landing-page test that lifts signups 30% but does not move that number after 60 days lands as a verdict of "no effect" in the archive, even though the headline lift was real.
Common mistakes
- Picking revenue as the north star.Revenue is a lagging indicator — by the time it moves, the product changes that drove the change are already old. A north star is leading by definition; revenue is what the leading indicator predicts.
- Having multiple north stars.Two north stars equals zero north stars. The whole point is forcing the team to commit. If two truly compete, decompose them into a single number that captures the tradeoff (e.g., "active workspaces at $20+ ACV").
- Treating the metric as the goal.The north star is a proxy for value, not value itself. If a team starts gaming it (e.g., bot-driven "active workspaces"), the metric has decayed. Re-anchor to the underlying customer behavior the metric was meant to capture.
Related terms
Pick a hypothesis. Vocabulary done.
The fastest way to learn this vocabulary is to commit one experiment. The contract takes about five minutes to write.