The best product teams know that good measurement is its own discipline. With the range of product metrics now available across acquisition, engagement, retention, and revenue, the work isn’t tracking more; it’s tracking what matters. The key metrics that move the product forward are usually a small, deliberate set. This blog walks through 20 product performance metrics worth tracking, grouped by what each one reveals. It also flags the vanity metrics worth being skeptical of along the way and the north star framework that should sit above them all.
Mohita Jaiswal - November 2018
Why Metrics Matter for Product Teams
How people actually use the product is the closest proxy product teams have to user intent. Stated assumptions get tested by real behavior — what people actually do, not what they say they will do. That’s why metrics matter: they convert opinions into evidence. But the risk is real. A dashboard full of numbers that move but don’t mean anything is worse than no dashboard at all. It gives the appearance of insight without the substance. The discipline isn’t tracking everything you can; it’s tracking what tells you whether the product is working.
Two distinctions help in deciding what to track: leading vs. lagging indicators. Lagging indicators tell you what already happened (revenue, churn); leading indicators tell you what’s about to happen (activation rate, time-to-second-action). Both matter, but leading indicators are what you can still act on. Another distinction is real metrics vs. vanity metrics. A vanity number isn’t a bad number on its own. It’s a number being used to answer a question it doesn’t actually answer. For instance, pageviews can look like demand and actually be confusion, whereas total signups can look like growth and actually be a leak.
Start With a North Star Metric
Before listing the 20, start with the one above them all. The north star metric is the single metric that best captures the value a product delivers to its users. It is what the entire team optimizes for. Every other metric should ladder up to it.
A few well-known examples:
- Spotify: time spent listening
- Airbnb: nights booked
- Slack: messages sent within paid teams
- Netflix: hours streamed per active user
- WhatsApp: messages sent
What these have in common: each captures value-delivered (the user gets something real) and ties cleanly to business success. Time spent listening means Spotify is solving a genuine need. Nights booked mean Airbnb is matching supply and demand. Without the North Star metric, every metric below it gets equal weight, which is the same as having no priority at all. The principle: pick the one number that, if it moves, tells you the product is succeeding for users and the business. That’s the metric the team rallies around.
Metrics That Show Whether Users Show Up
Top-of-funnel reach matters, but only if it leads somewhere. These four metrics measure presence, that is how many users are engaging with the product at all.
1. Daily active users (DAU)
Users who engage with the product on a given day. The most immediate read of whether the product is part of someone’s habit. Daily active users is also one of the most widely benchmarked figures in product analytics.
2. Monthly active users (MAU)
Users who engage at least once in a 30-day window. Monthly active users give the broader picture of reach across the user base.
3. DAU/MAU ratio (stickiness)
What percentage of monthly users come back daily. A high MAU with low stickiness signals a leaky bucket — people are arriving, but they aren’t coming back often.
4. New user signups
That’s top-of-funnel growth. Useful as a directional signal, but never useful alone.
Metrics That Show Whether Users Stay
This is the most important category in product measurement. Anyone can acquire users. The real question is whether they come back.
5. Customer retention rate
The percentage of users who continue using the product over a defined period. Customer retention rate is the cleanest measure of whether the product earns its place in someone’s life.
6. Churn rate
The inverse of retention. The percentage of users who stop using the product in a given period. Churn rate is often the first metric to break before broader growth slows.
7. Cohort retention curves
How a specific group of users behaves over time, not just at month one. The shape of the curve matters more than the first month’s number — a curve that flattens means you have real product-market fit; one that keeps declining means you don’t.
8. Time-to-second-action
How quickly a new user takes a meaningful second action after signing up. The strongest leading indicator of whether users return for a third, tenth, or hundredth time.
Metrics That Show Whether Users Engage
Presence isn’t engagement. These four metrics measure depth, how meaningfully users interact with the product once they’re there.
9. Feature adoption rate
The percentage of users who use a specific feature within a defined window. Feature adoption rate is the cleanest signal of whether the new product worked or didn’t.
10. Session length
How long the average session lasts. Useful only when paired with task completion, long sessions in a checkout flow are a problem, not a win.
11. Frequency of use
How often the average user engages over a defined period. The other half of the engagement equation, alongside session length.
12. Activation rate
The percentage of new users who hit the “aha” moment — the first meaningful experience that demonstrates product value. Often, the strongest predictor of retention down the line.
Metrics That Show Whether the Product Makes Money
Engagement without revenue isn’t a sustainable business. These four metrics tie product behavior to financial outcomes.
13. Conversion rate
The percentage of users who complete a defined revenue or value action — purchase, upgrade, signup, whichever matters most. Conversion rate is the headline number for any monetization flow.
14. Customer acquisition cost (CAC)
What it costs the business to acquire a paying customer, across paid and organic channels. Rising customer acquisition cost with flat conversion is an early warning sign.
15. Average revenue per user (ARPU)
Total revenue divided by active users. Average revenue per user tracks whether the average user is becoming more or less valuable over time.
16. Customer lifetime value (LTV)
The total revenue expected from a single customer across their relationship with the product. Most useful in ratio with CAC, the LTV-to-CAC ratio is what tells you whether the business model works.
Metrics That Show Whether the Product Works
Behind every other category sits the question of whether the product itself functions well. These four metrics measure the UX layer of product performance.
17. Task completion rate
The percentage of users who finish a defined task — checkout, signup, file upload, whatever the flow is. Often, the first place a product problem shows up, before it leaks into churn or stalled conversion.
18. Time on task
How long it actually takes a user to finish a task. Tracked over time, it reveals whether the experience is getting better or worse.
19. Error rate
How often users encounter errors — broken states, validation failures, dead ends. Errors are friction, and friction is the slow form of churn.
20. Form and cart abandonment
Where users drop out of high-intent flows. A high abandonment rate in a checkout or onboarding flow is one of the most actionable signals a product team can have.
The Vanity Metrics to Watch Out For
For each useful metric, there’s a tempting one nearby that doesn’t earn its place. We call them the vanity metrics. Four worth naming honestly:
1. Pageviews
A high count can mean genuine interest. It can also mean people are bouncing between screens trying to find something they couldn’t.
2. Time on site (standalone)
3. Total signups
A top-of-funnel number that says nothing about whether anyone stuck around. The gap between signups and active users is where most products fail quietly.
4. Total downloads
Installs aren’t usage. A product with millions of downloads and a 30-day retention rate of 5% is not a successful product. It’s a marketing success and a product failure.
The pattern across all four: they are easy to track, satisfying to report, and decoupled from whether the product is actually working. They aren’t always wrong. They just aren’t enough on their own.
“Numbers that move are easy. Numbers that mean something are the work. Most teams chase the first and call it the second, and a dashboard rewards them for it.” — Deepali Saini | CEO at Think Design Collaborative
How to Pick the Right Metrics for Your Product
Here’s a short, practical framework for choosing what to track:
1. Start with the objective
What does product success look like for this team this quarter? Not in general, specifically.
2. Define the user behavior that signals it
What do users actually have to do for that success to be real?
3. Make it measurable
Specific, time-bound, segmentable by cohort.
4. Pick a north star, then ladder up
5. Audit quarterly
The right metrics for last quarter may not be the right ones now. The discipline is reviewing the list, not just the values inside it.
Choosing the right metrics is its own practice; learning how to determine which KPIs to use is exactly what larger teams are looking for.
