PM Gym

Metrics

Pick the number that actually tells you the truth

Not all metrics are equal. Some tell you what's about to happen; some only tell you what already happened. Some can be gamed into looking good while the product quietly gets worse. This guide covers how to choose metrics you can actually trust and act on.

Step-by-step lessons

Choose Metrics You Can Trust

Four short lessons: what makes a good metric, the main types, picking a North Star, and matching a metric to a decision.

1

What Makes a Metric Good

Before adopting any metric, run it through three checks — the 3 A's.

A1

Actionable

A specific decision can actually move it — it's not just a number that sits there.

A2

Accessible

Easy to get and understand, not buried in a report only one analyst can pull.

A3

Auditable

You can trace it back to source data and trust it's counted consistently.

Quick check

A team tracks "total page views, all-time" as their main dashboard metric. Which of the 3 A's does it fail hardest?

2

Leading vs. Lagging, Input vs. Output

Metrics differ in when they tell you something, and in what part of the system they describe.

Leading indicator

Moves first, predicts a future result — e.g. trial signups predicting future revenue.

Lagging indicator

Confirms what already happened — e.g. quarterly revenue.

Input metric

Something the team directly controls — e.g. features shipped.

Output / outcome metric

The result inputs are meant to produce — e.g. activation, retention.

Quick check

Quarterly revenue confirms how the last three months went, but by the time you see it, the quarter is over. What kind of metric is this?

3

Choosing a North Star Metric

A North Star metric is the single number that best captures the core value your product delivers to customers, correlated with long-term business success.

Not revenue directly, but what leads to it

Spotify tracks time spent listening. Airbnb tracks nights booked. Neither is revenue itself — both are the moment a customer actually gets the core value the product promises. When that number is healthy, revenue reliably follows.

A North Star isn't your only metric, and a shallow proxy like "app opens" — easy to measure but disconnected from real value — is a common trap.

Quick check

A team picks "number of app opens" as their North Star, even though users often open the app, get frustrated, and leave without doing anything useful. What's the problem?

4

The Right Metric for the Decision

There's no single metric that fits every decision. Before reaching for a number, ask what decision it's actually meant to inform.

Judging a pricing test needs a different metric than judging an onboarding redesign. Match the metric to the decision, don't default to whichever number is already on the dashboard.

Quick check

A team wants to judge whether a new onboarding flow works, and defaults to checking "total company revenue" a week later. What's wrong with this metric choice?

Review the concepts

Metrics Flashcards

6 cards covering the essentials. Click a card to flip it.

Foundation Card 1 of 6

The 3 A's

Click to flip

Tip: say the answer out loud before flipping.

Explanation

In practice

1 / 6
Apply what you learned

Practice Scenarios

15 situations that test whether you can spot a bad metric, tell leading from lagging, or match a metric to the decision it needs to inform.

Scenario 1

A team's dashboard headlines "total signups since launch," which has risen every month for three years, even during a period when the product was clearly declining.

What kind of metric is this, and what's the risk?

Scenario 2

A team wants a metric to catch problems early enough to react, not just confirm results after the fact.

What type of metric should they prioritize?

Scenario 3

A support team is evaluated purely on "tickets closed per hour," and closures soar while customer satisfaction quietly drops.

Which of the 3 A's does this metric fail?

Scenario 4

A PM proposes "employee happiness with the roadmap" as the company's North Star metric.

What's the issue?

Scenario 5

A team wants to evaluate a pricing-page redesign and defaults to checking "monthly active users" a week later.

What's the concern with this metric choice?

Scenario 6

A metric is described as: "the number our finance team can trace back to raw transaction records at any time, with a documented calculation method."

Which of the 3 A's does this describe?

Scenario 7

A growth team reports "trial signups are up 30% this week" and predicts a strong revenue quarter.

What kind of metric are they using to make that prediction?

Scenario 8

Airbnb famously tracks "nights booked" rather than just "signups" as closer to its North Star.

Why is "nights booked" the better choice?

Scenario 9

A team's "onboarding completion rate" has been flat for months, and they're debating whether it's a leading or lagging indicator of retention.

What's the right way to think about it?

Scenario 10

A stakeholder asks for "one metric that tells us everything about how the product is doing."

What's the realistic response?

Scenario 11

A metric named "engagement score" turns out to be calculated differently by two different teams, with no shared documentation.

Which of the 3 A's is this failing?

Scenario 12

A team is deciding between raising prices or improving retention, and someone suggests checking "daily app opens" to guide the choice.

Is this the right metric for this decision?

Scenario 13

A team notices their North Star metric has been rising for six months, but customer support tickets about frustration have also been rising just as fast.

What should the team do?

Scenario 14

A junior PM says "let's just track everything so we don't miss anything important."

What's the issue with this instinct?

Scenario 15

A team wants to A/B test a checkout redesign and picks "checkout completion rate" as the metric to judge success.

Is this a good match?

Lock it in

Guess the Term

Read the clues and name the concept. The fewer clues you need, the more points you score.

Round 1 Score 0
Keep it handy

Metrics Quick Reference

The whole topic on one screen.

The 3 A's of a Good Metric

A

Actionable

A decision can actually move it.

A

Accessible

Easy to get and understand.

A

Auditable

Traceable to source data, trusted.

Leading vs. Lagging

Leading

Moves first, predicts what's coming.

Lagging

Confirms after the fact — too slow to react to.

Choosing a North Star

Captures core value

The moment a customer gets real value.

Correlates with success

Healthy North Star, healthy business.

Avoid shallow proxies

"App opens" isn't the same as value delivered.

Matching Metric to Decision

Ask what decision it informs

Before picking any metric.

Prefer close, isolatable metrics

Over distant, indirect ones.

Pair with guardrails

No single number tells the whole story.

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