How do I use data to inform product decisions?

Key product metrics that matter


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Key product metrics that matter

Measuring what drives real progress

As businesses grow, the amount of data available increases rapidly. The challenge is not access to metrics — it is knowing which ones matter.

Focusing on the wrong metrics can create false confidence. Focusing on the right ones helps founders understand whether the product is creating real value and where to improve.

The goal is not to track everything, but to track what informs better decisions.


What makes a metric meaningful?

A meaningful product metric should:

  • reflect real customer behaviour
  • link to business outcomes
  • help guide decisions

Metrics that do not influence action are unlikely to add value.


The product metrics framework

Founders should focus on four key areas when assessing product performance:

  1. Engagement

Engagement measures how actively customers use the product.

This may include:

  • frequency of use
  • time spent in product
  • key actions completed

Strong engagement indicates that the product is becoming part of the customer’s workflow.

Common mistake: Measuring sign-ups rather than actual usage.

  1. Retention

Retention is one of the clearest indicators of product value.

It answers:

  • Do customers keep using the product over time?
  • Do they return regularly?

Improving retention is often more valuable than increasing acquisition.

Common mistake: Focusing on growth while ignoring churn.

  1. Conversion

Conversion measures how effectively the product turns interest into action.

This might include:

  • trial to paid conversion
  • onboarding completion
  • progression through key steps

Strong conversion indicates that the product is easy to understand and delivers value quickly.

Common mistake: Driving traffic without improving conversion rates.

  1. Revenue quality

Revenue should be assessed beyond headline numbers.

Key considerations include:

  • recurring vs one-off revenue
  • customer lifetime value (LTV)
  • pricing acceptance
  • expansion or upsell

This helps founders understand how sustainable growth is.

Common mistake: Relying on top-line revenue without understanding underlying drivers.


Leading vs lagging indicators

Not all metrics provide the same type of insight.

Leading indicators

  • engagement
  • onboarding completion
  • feature usage

These signal future performance and help guide early decisions.

Lagging indicators

  • revenue
  • churn
  • profitability

These confirm outcomes but are slower to change.

A strong product strategy uses both but places emphasis on leading indicators to guide action.


A simple test: the decision question

Ask:

Does this metric help us decide what to do next?

If not, it may not be worth prioritising.

Metrics should inform:

  • what to build
  • where to improve
  • when to invest

How metrics evolve as you scale

Early stage

Focus: Learning

  • engagement
  • early usage patterns
  • qualitative feedback

Product-market fit stage

Focus: Validation

  • retention
  • repeat usage
  • conversion

Growth stage

Focus: Scaling

  • acquisition efficiency
  • revenue growth
  • customer lifetime value

Scale-up stage

Focus: Optimisation

  • margins
  • efficiency
  • long-term value creation

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