Unit 9: Metrics and measurement: knowing if you're winning

Learning objectives

By the end of this unit, you should be able to define meaningful product metrics tied to outcomes, distinguish between vanity metrics and actionable metrics, and set up a basic measurement framework for a product or feature.

Video script

Reading material

The metrics hierarchy

Product metrics work best when they're organized in a hierarchy that connects daily team metrics to business outcomes.

North star metric. The single metric that best captures the value your product creates for users. For a collaboration tool, it might be "teams completing shared workflows per week." For a marketplace, it might be "successful transactions per month." The north star should reflect user value, not just business value, because user value is what drives business value over time.

Input metrics. The metrics that feed into your north star. These are the levers your team can directly influence. If your north star is "successful transactions per month," your input metrics might include "new listings created," "buyer search success rate," and "seller response time." Each team owns one or two input metrics and optimizes them.

Health metrics. The metrics that tell you if your product is functioning well overall. Performance (load times, error rates), support volume, and satisfaction scores. These aren't the metrics you optimize for, but they're the metrics that tell you if something is broken.

Business metrics. Revenue, costs, margins, growth rates. These are what leadership and the board track. Product teams should understand how their work connects to business metrics, but they shouldn't optimize directly for them because business metrics are lagging indicators that move too slowly to guide product decisions.

Common measurement mistakes

Measuring too many things. Teams that track 40 metrics track zero metrics. Information overload leads to metric fatigue, where nobody looks at the dashboard because it's overwhelming. Pick 3-5 metrics that matter and ignore the rest.

Measuring outputs instead of outcomes. "We shipped 12 features this quarter" is an output metric. It tells you the team was busy. It tells you nothing about impact. "Three of our five target metrics improved this quarter" is an outcome metric. It tells you the team was effective.

Not measuring at all. Some teams ship features and never check whether they worked. They move on to the next thing and assume impact. This is how products accumulate features that nobody uses, which increases complexity without increasing value.

Practical exercise

Exercise: Design a measurement framework

Choose a product or feature (real or from a previous exercise). Design a measurement framework by answering these questions.

1. What's the north star metric? What user behavior does it capture?
2. What are 2-3 input metrics that your team could directly influence? How do they connect to the north star?
3. What are 1-2 health metrics you'd monitor?
4. How would you know if a feature you shipped was successful? Define a specific success criterion with a metric and target (e.g., "Activation rate increases from 40% to 55% within 60 days of launch").
5. How often would you review these metrics? Who should be in the review?

Write this up as a one-page measurement plan. The goal is to practice connecting metrics to strategy and making them specific enough to actually guide decisions.