Digital product strategy: metrics and KPIs in practice

Most product dashboards I see have the same problem: they're full of numbers and empty of decisions. They track dozens of indicators and yet no one can tell them what to do with them on Monday morning.

This happens because measuring has become an end in itself. We adopt an analysis tool, configure everything it offers and that's it, we have metrics. What's missing is the bridge between the number on the chart and the decision it should guide. Without this bridge, metric is decoration.

The thesis of this text is practical: a good KPI is not the one that measures the most things, it is the one that changes decisions and connects directly to the product strategy. I want to show you how to move from the decorative panel to a set of indicators that effectively guide the work.

Start with strategy, not metrics

The most common mistake is to start by asking “what can you measure?”. The right question is the opposite: “what are we trying to achieve?” The metric comes after, as a consequence of the strategy, never before it.

A product that wants to grow its base measures different things from a product that wants to deepen the use of those who already have it. One that seeks to make money measures differently than one that still validates the proposal. When metrics come before strategy, you end up optimizing numbers that lead nowhere.

This means a simple and rare exercise: before assembling any panel, write in one sentence what the product needs to achieve during this period. Only then ask what indicators prove whether you are getting there. This order changes everything.

Result metric and movement metric

A common mistake is mixing two types of indicators that serve different purposes.

Result metrics tell you whether you reached your objective, revenue, retention, active base. They are important, but they have a defect: they arrive late. When retention drops, the damage has already been done.

Movement metrics are those that you can directly influence on a daily basis and that, it is believed, lead to results. How many users complete onboarding, how often they use the main function, how long it takes until the first valuable action.

You monitor the results to know if the strategy works, and movement to have something to adjust while there is still time. A results-only panel is a rear view mirror. You also need what's in front of you.

Connecting the two in a logical chain

Maturity appears when you can draw the chain: this action that we measure today plausibly leads to this result that we want tomorrow.

For example: we believe that users who complete a profile have better retention. We then track the profile completion rate (movement) with the expectation of moving retention (result). If the chain confirms with the data, great. If not, the hypothesis was wrong and you learned something valuable, cheap.

How to choose the few KPIs that matter

Inflated panel is a symptom of lack of priority. In practice, the discipline is to cut.

One way that works is to define, per period, a main metric, the one that best summarizes whether the product is moving in the direction of the strategy. Around it, a small set of supporting indicators that help you understand why. The rest is available for investigation, but outside the decision panel.

This focus avoids the classic problem of optimizing one metric at the expense of another without realizing it. Pushing registrations can inflate the base and sink activation. Speeding up a sale can ruin retention. When there is a main metric linked to the strategy, these sacrifices become visible and become a conscious decision, not an accident.

The practice of reviewing and distrusting numbers

Metrics are not absolute truth; it is an imperfect measure of something that matters. Treating it as truth leads to bad decisions with the appearance of rigor.

It is worth maintaining two habits. The first is to be suspicious of sudden movements: before reacting to a jump or fall, check that it is not a measurement problem, a change in instrumentation or an external effect. Many hasty decisions were born from a graph that lied.

The second is not to outsource understanding to the number. The data tells what happened; he rarely says why. Combining quantitative metrics with direct conversations with users is what transforms data into an informed decision. Those who only look at the panel decide in the dark with the light on.

The data dimension that cannot be ignored

Measuring a product means collecting people's behavior, and this, in the Brazilian context, speaks directly to LGPD. In practice, putting together a metrics strategy includes deciding what to collect, why, for how long and on what legal basis.

It's not bureaucracy separate from product work, it's part of it. Collecting more data than necessary, “just in case”, is accumulating risk without return. The question “does this metric change a decision?” Therefore, it has a brother: "is this data that we collected justified in the eyes of those who entrusted it to us?"

A mature metrics strategy is also a responsible collection strategy. The two go together.

The danger of optimizing what is easy to measure

There is a silent bias that distorts many product strategies: we tend to give importance to what is easy to measure, not what actually matters. The result is that convenient indicators gain disproportionate weight, and dimensions that are difficult to quantify, trust, satisfaction, perceived value, disappear from the radar.

This leads teams to optimize for clicks, screen time and number of sessions, because these numbers are simple to capture, while ignoring whether the product is actually solving people's problems. An app can increase usage time because it is confusing and the person needs more time to do the same thing. The number goes up; the experience gets worse.

The defense against this bias is to be suspicious when an easy metric becomes the star of the panel. It's worth asking: is this rising number good for the user or is it only good for our graph? Combining quantitative indicators with qualitative signals, research, conversations, observation, is what avoids optimizing the convenient at the expense of the important. Mature product strategy measures what matters, even when measuring is difficult.

From the decorative panel to the panel that decides

In the end, the difference between a team that measures well and one that only has dashboards is cultural, not tooling. It's not about having the most sophisticated platform; It's about the discipline of linking every number to a decision and every decision to a strategy.

Metric that no one uses to decide should leave the panel. Metrics that change what you do deserve attention and care. This constant triage is the real work, and it's what separates product strategy from product theater.

Start small: Choose the one metric that, if changed today, would make your team act differently this week. Build from there. The rest is refinement.

If your product dashboard is full of numbers and poor in decisions, it's worth talking about how to reconnect it to strategy. On the blog there are other texts about metrics, experimentation and product management that deepen this practical approach.