In product management, metrics often become a formality. Everyone tracks something. Dashboards are built, reports are sent. But the real problem is not the lack of data — it’s that metrics rarely influence decisions.
A metric is not a number. It’s a signal that changes behavior. The right metric doesn’t just reflect progress. It drives it.
A Metric Is a Decision with Consequences
In my experience, I’ve seen many teams with "movement" — but no change. They track LTV, NPS, MAU — but nothing shifts in their process, focus, or priorities.
Metrics shouldn’t prove that you’re doing well. They should point to where, how, and why you’re not there yet.
Why measure product success at all?
Not all products are built to scale, grow revenue, or lock users in. But every product exists to solve a specific problem. That’s your true North Star.
A metric isn’t just an answer to “how are we doing?” It’s a way to ask: “Is what we’re doing actually working?” If yes — a good metric will show that. If not — it will expose the gaps.
Common mistakes when choosing metrics
- Metrics without behavioral value If a metric doesn’t change behavior or decisions, it’s noise.
- Metrics based on theoretical success Teams often borrow metrics like LTV, NPS, DAU without checking if they’re relevant to their model.
- Metrics that track process, not impact Number of features released, development time, number of A/B tests. Good for internal audits, not for understanding user value.
Case 1. A metric that didn’t drive change
In one project, we tracked the number of tasks created by users. The logic: more tasks = more engagement. But soon, we saw:
- churn increasing
- support tickets piling up
- satisfaction scores falling
We dug deeper and found the issue: users were starting tasks — but not completing them. We shifted focus to task completion rate, and suddenly the real picture emerged: – users entered the product but never reached value.
Lesson: activity ≠ value.
Real insight comes from the “moment of truth” — not the first action.
Case 2. A metric that changed team behavior
In a B2B product, we used MAU as our core success metric. Numbers looked stable, but the product felt stuck.
User interviews showed that most people logged in just to check status. No interaction, no meaningful value the product had become a "dashboard," not a tool. We switched to a more relevant metric: % of users performing a core action weekly. That simple shift led to:
- sharper design decisions
- better copy and onboarding
- 45% increase in weekly core usage
Lesson: reach ≠ relevance.
A metric should provoke rethinking — or it’s useless.
Case 3. When LTV and Retention don’t make sense
In one B2C product, we tracked LTV and 30-day Retention. But the model was simple: users came in, booked a consultation with an expert, paid and left.
No subscriptions. No long-term cycle. LTV looked low. Retention dropped. It seemed like failure. But user interviews revealed the opposite: One session delivered full value.
We shifted focus to a better metric: Conversion-to-value, % of users who completed a successful consultation on first try. And measured NPS immediately after the session, not 30 days later.
Lesson: the metric must fit the usage context.
If the value is delivered in one session — retention isn’t the point. Value is.
Quantitative and qualitative methods work best together
Numbers show what’s happening. But only research shows why.
Quantitative metrics bring scale and objectivity. Qualitative methods bring context, depth, and meaning.
Before choosing a metric, pause and zoom out:
- run a cohort analysis — to see who actually stays and why
- review the CJM and use cases — to understand what you're really building and for whom
- gather user voice — interviews, open feedback, spontaneous comments
- observe real usage — what users do, where they stop, what they ignore
- analyze support requests — that’s often where the truth shows up
This isn’t preparation for metrics. It’s discovering what matters. Because a metric only works when you understand what you're measuring.
How to pick a metric that actually works
- Start with: What do we want to change? Metrics must reflect real shifts in behavior, business, or user experience.
- Ask: Will this metric influence a decision? If you measure something — will it drive prioritization, redesign, or action?
- Tie it to a moment of truth Every product has a point where value is felt. Focus your metric there.
- Avoid vanity metrics. Choose action metrics. If it’s only for reports — it’s dead. If it drives change — it’s alive.
Examples of meaningful metrics
- Activation rate — % of users who reach the first value point
- Time to value — how long it takes to deliver that value
- Retention after 3/7/30 days — are users coming back?
- Support contact per feature — where friction lives
- Task success rate — can users complete key actions without help?
A metric is a mirror is not a trophy
Numbers don’t prove you’re right. They show the link between actions and results. If that link isn’t clear — it’s not the metric’s fault. It’s how you’re reading it.
A good metric isn’t a pretty dashboard number. It’s a small signal that makes your team ask “Are we really moving in the right direction?”
Final thoughts
A metric isn’t an outcome. It’s a trigger. Not a report but a feedback loop. Not a decoration — but a prompt for deeper questions. Because a product doesn’t grow on its own. It grows where it’s measured with understanding.
→ A metric is a point of impact. Not just a number.