Many product teams are drowning in data but starving for insight. They track dozens of metrics, yet struggle to answer fundamental questions about direction, impact, and focus. The problem is most of the data is disconnected from their strategy.
Metrics have become performance theatre. They’re used to fill reports, justify backlogs, or satisfy executive curiosity. But the best teams use metrics differently. They select them to support thinking, learning, and decision-making. When done well, metrics drive strategy—they don’t just report on it.
Product metrics only make sense in the context of a well-defined strategy. That means starting with a clear understanding of who the product serves, what problem it solves, and how success will be measured.
From that foundation, useful metrics emerge as hypotheses. If your product goal is to reduce onboarding friction, you need to measure activation rate, time to value, and points of drop-off. If you’re scaling a platform, prioritise engagement depth and system health—not just user growth.
Structuring your metrics around input, output, and outcome helps teams stay grounded:
This framing ensures you’re not just tracking what happened, but why it matters.
A long list of metrics creates noise. Most teams need fewer numbers—but better ones.
Prioritise three to five metrics per product. Each one should be directly tied to a decision the team might make. If a number goes up or down, it should prompt a discussion: What’s changed? What do we do next?
Avoid vanity metrics—those that look good on charts but don’t reflect meaningful progress. Total sign-ups, app downloads, or MAUs without context often mislead more than they inform.
The right metrics surface friction, reveal opportunity, and support focus.
Metrics work best in layers.
Leading indicators show you what might happen—early signs of user behaviour shifting or product-market fit improving. These include metrics like feature adoption or time spent on a key flow.
Lagging indicators confirm that change has happened. These are typically business outcomes like churn, revenue per user, or renewal rate.
Good product leaders track both. Leading indicators drive iteration; lagging ones validate strategic direction. Relying too heavily on either creates blind spots—one tells you too late, the other lacks certainty.
Even strong metrics lose their power if they’re locked in inaccessible dashboards or lack narrative context.
The best teams create shared, interpretable views:
Avoid technical silos. Metrics should bridge disciplines, not reinforce separation.
Metrics shouldn’t just be used in reviews. They should inform everyday decisions. The most effective product teams reference key metrics during:
It’s not enough to have metrics. Teams need to build metrics fluency—the habit of using data to reason, reflect, and adjust course.
When designed intentionally, the right metrics align teams, clarify focus, and support better decisions at every level. They give leaders confidence—not because they show success, but because they reveal the truth.
Start here:
Data is helpful. But it’s the right metrics, in the right conversations that move product forward.