Product Metrics That Matter (And the Ones to Ignore)
- What product metrics are actually for
- Why most teams track the wrong things
- The five metrics that actually predict product health
- How to make metrics review a daily habit
Most product dashboards resemble a museum of vanity metrics — page views, signups, monthly active users (MAUs), and net promoter scores (NPS) that clutter screens but rarely drive meaningful action. These metrics might look impressive on paper, but they often obscure the core question: Is this product actually delivering value? The metrics that matter are fewer in number, challenging to manipulate, and often uncomfortably revealing. They provide the insight necessary to tell whether your product is truly working for your users.
What Product Metrics Are Actually For
At their core, product metrics exist to answer one pivotal question: Is this thing getting better? It's not about busywork or superficial engagement; it’s about whether the product is improving its ability to fulfill its promise to users.
The startup culture of the 2010s blurred the lines between activity and health. Companies celebrated rising numbers: more pageviews, higher MAUs, and an influx of signups. However, behind these numbers, retention rates often declined, leading to disastrous outcomes. Andrew Chen of Andreessen Horowitz has extensively highlighted this issue. The metrics that truly predict survival are not the flashy ones but rather retention curves, weekly active percentages, and time-to-value metrics.
A useful metric possesses three key attributes: it’s actionable, accessible, and auditable. Unfortunately, many metrics on product dashboards fail to meet at least one of these criteria.
Why Most Teams Track the Wrong Things
Vanity metrics are tantalizing because they show growth. New users, total signups, and app downloads can create a false sense of security. These are stock metrics — numbers that typically trend upward. But they fail to provide insight into the actual value of each new user.
Conversely, retention metrics are flow metrics — they can shrink, and they often do. Monitoring retention is uncomfortable because it forces teams to confront user loss, a reality no one wants to face.
Another problem is dashboard inflation. Teams often add metrics quarterly without removing outdated ones. Over time, a dashboard can balloon to include dozens of metrics, leaving teams confused about which ones matter. Decisions become vague and based on gut feelings rather than data-driven insights.
Finally, metrics without targets are merely decorative. For instance, stating that “activation rate is 32%” is devoid of context. However, framing it as “activation rate is 32%, our target is 50%, and we’re testing onboarding changes monthly” makes it actionable and purposeful.
This approach aligns closely with strong product thinking; metrics should always stem from a clear question or hypothesis.
The Five Metrics That Actually Predict Product Health
While there are many metrics available, here are five critical ones that every product team should know and monitor:
-
Day-7 (or Week-1) Retention: This metric measures the percentage of users who signed up within a week and are still using the product after seven days. If your B2B SaaS product's retention falls below 30%, it signals a value problem rather than a growth issue.
-
Time-to-First-Value (TTFV): How long does it take for new users to achieve the primary value of your product? If TTFV exceeds 10 minutes for a self-serve product, it’s a strong indicator that retention will suffer.
-
Weekly Active Percentage of Paid Accounts: For B2B SaaS, track the percentage of paid seats that logged in over the past week. If this number dips below 60%, churn may be on the horizon; below 40% indicates churn is already occurring but is not yet visible due to ongoing contracts.
-
Net Revenue Retention (NRR): This metric looks at the revenue from customers you had a year ago, accounting for churn and upsells. An NRR above 110% means existing customers are expanding faster than they are leaving. Below 100% indicates a leaky bucket situation.
-
Feature Adoption of Your Top Use Case: For your product's most critical feature, assess what percentage of active users have utilized it in the last 30 days. If only 12% of users are engaging with your "core feature," it may be misclassified.
These five metrics form the foundation for understanding product health. Everything else is supplementary.
How to Make Metrics Review a Daily Habit
A metric you review quarterly is one you won’t act on. Successful teams commit to reviewing metrics weekly at a minimum. Start with a one-page weekly report that highlights the five essential metrics. Distribute it every Monday morning, ensuring it can be read in 90 seconds.
Each metric should have a target and an assigned owner. Without ownership, metrics stagnate. Without targets, metrics remain unmoored from action.
Consider implementing micro-learning to ease the transition. Rather than revamping your entire metrics stack in one fell swoop, focus on one metric each week. Make it actionable, set a target, and find an owner. After a month, move on to the next one. This gradual approach nurtures a culture of measurement without overwhelming the team.
Hold a 30-minute weekly metrics review that is open to everyone. Use this time to discuss the latest report, analyze changes, and decide on tests to run. This meeting can transform how your team interacts with metrics, shifting from passive observation to active engagement.
When a metric declines, ask three key questions: Is this real? Is this temporary? What’s our hypothesis for the change? You don’t need immediate answers; the goal is to generate hypotheses to explore.
What Good Measurement Looks Like in Practice
You’ll know you’re on the right track when conversations pivot from debating which metrics to look at to discussing the implications of those metrics. Instead of arguing about whether NPS is the right measure, the discussion shifts to analyzing why day-7 retention dropped last week.
Mature product teams tend to have shorter dashboards, not longer ones. They’ve learned to ignore metrics that don’t matter. Decisions become swifter and more confident, focusing on actionable insights rather than endless debates.
Instead of celebrating superficial milestones like “10,000 signups this month,” the focus shifts to more meaningful metrics, such as “1,200 of those activated, and here’s our ongoing testing strategy.” This shift may be less glamorous, but it’s far more sustainable.
Cohort analysis becomes standard practice. Aggregate metrics fade away as teams begin to understand the nuances of user behavior over time. By cohorting data based on signup week, plan tier, or use case, teams can better address changing patterns.
Ultimately, good measurement encourages teams to confront uncomfortable truths. A retention curve that flattens at 40% after week four indicates stable value for real users. Conversely, a declining curve suggests the product has failed to deliver value, prompting necessary introspection.
Conclusion
The right metric is often the one that’s uncomfortable to look at but has the potential to change your focus and actions for tomorrow. By honing in on the metrics that truly matter, product teams can make informed decisions that drive real value for users.
Ready to improve your product measurement and decision-making skills without the overwhelm? Take the Omie Skill Assessment today and discover tailored lessons designed just for you!