Open this lesson in your favourite AI. It'll walk you through the why, explain the demo, and quiz you on the try-it list.
Teams without a North Star metric optimize for the metric that's easiest to move, not the one that reflects real value delivery. A well-chosen NSM is the single number that correlates with long-term retention and revenue — it aligns product, engineering, and growth around one honest signal instead of a dashboard full of vanity metrics.
Evaluate three NSM candidates for a B2B SaaS and score them on leading vs. lagging quality.
Use these three in order. Each builds on the one before.
In one paragraph, explain what a North Star metric is like I'm new to it.
Walk me through how to select a North Star metric step by step — the criteria, the pitfalls, and how to validate the choice.
Given a marketplace that has both buyer and seller activity, how would you choose a single North Star that reflects health for both sides without collapsing into a vanity metric?
type NSMCandidate = {
name: string;
leadsRevenue: boolean; // true = leading indicator
userControlled: boolean; // true = users drive it, not the company
measurableWeekly: boolean;
};
const candidates: NSMCandidate[] = [
{ name: "MRR", leadsRevenue: false, userControlled: false, measurableWeekly: true },
{ name: "Weekly Active Projects", leadsRevenue: true, userControlled: true, measurableWeekly: true },
{ name: "Invites Sent per Account", leadsRevenue: true, userControlled: true, measurableWeekly: true },
];
candidates.forEach(c => {
const score = [c.leadsRevenue, c.userControlled, c.measurableWeekly].filter(Boolean).length;
console.log(c.name, "→ score:", score, "/3");
});
// MRR → score: 1 /3
// Weekly Active Projects → score: 3 /3
// Invites Sent per Account → score: 3 /3