Definition
Product Analytics Metrics
Product analytics metrics are the standard measures of product health derived from event data: activation rate (new users reaching first value), retention (users still active after N periods), engagement (frequency and depth of core actions), conversion (completion of key flows), and the north-star tree that ties them to strategy.
Interactive diagram - hover the elements. Plotted values are illustrative examples, not measurements.
Which metrics form the core set?
Five families cover most products. Activation: share of signups reaching the defined first-value moment. Retention: cohort share still active at N days/weeks. Engagement: core actions per active user per period (DAU/MAU ratio is the blunt version). Conversion: step-through rates of named funnels. Monetization bridges: value events per retained user. Everything else is a segmentation or decomposition of these.
What are the classic metric mistakes?
Counting activity instead of value (logins as engagement), averaging across mixed populations (blending power users with tourists), comparing retention numbers computed under different definitions, and shipping metrics no one owns. The corrective habit: every reported metric carries its definition, its owner, and its decision - what would change if it moved?
In practice: Our training cohorts end with each PM shipping a reviewed analysis of these exact metrics on their own product.
Product Analytics Metrics: common questions
What is a vanity metric?+
A number that moves without value being created - cumulative downloads, registered users, page views. The test: can it go up while the business gets worse? If yes, it can decorate a slide but shouldn't steer a roadmap.
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