Metrics & Measurement

Track the numbers that tell you whether the product is actually working.

How to use

• /metrics-measurement Apply metrics measurement constraints to this conversation.
• /metrics-measurement <product> Design a metrics framework for the described product.

Constraints

Metric Hierarchy

Structure metrics in layers:

• North star: the one metric that captures your product's core value delivery
• Health metrics (3-5): the vital signs of product health — retention, activation, engagement, revenue
• Feature metrics: per-feature adoption, usage, and satisfaction
• MUST have a clear north star. If you track 20 metrics equally, you track none.
• Each metric SHOULD connect to the one above it in the hierarchy

Metric Selection

• MUST choose metrics that are actionable — the team can influence them through their work
• MUST choose metrics that are understandable — everyone on the team can explain what they mean
• SHOULD prefer leading indicators over lagging ones (activation rate predicts revenue better than revenue itself)
• NEVER pick a metric just because it's easy to measure. Measure what matters, not what's convenient.
• MUST include at least one counter-metric to prevent gaming (e.g., if optimizing signup rate, also track 7-day retention)

Instrumentation

• MUST define how each metric is calculated before tracking it. Ambiguous definitions create bad decisions.
• SHOULD document: data source, calculation method, known limitations, update frequency
• MUST ensure data accuracy. Bad data leads to confidently wrong decisions.
• SHOULD automate dashboards. Metrics that require manual calculation don't get checked.
• NEVER ship a feature without instrumenting the metrics that tell you if it worked

Review Cadence

• North star: review weekly with leadership
• Health metrics: review weekly with the product team
• Feature metrics: review post-launch and monthly thereafter
• MUST set alerts for significant changes — don't wait for the weekly review to discover a cliff
• SHOULD do monthly deep dives on metric trends, not just snapshot checks

Anti-Patterns

• Vanity Metrics: total users, downloads, page views — numbers that go up but don't correlate with value
• The Dashboard Nobody Checks: building dashboards and never looking at them
• Too Many Metrics: tracking 50 things and losing sight of what matters
• Metric Fixation: optimizing a number while ignoring the experience behind it
• The Misleading Aggregate: one number hiding completely different segment behaviors