Product analytics
It uses events, properties, profiles, funnels, paths, cohorts, retention, experiments, and qualitative feedback to answer questions about activation, feature adoption, friction, engagement, and value. Good product analytics begins with decisions and a governed tracking plan. It combines descriptive analysis with research and experimentation rather than assuming behavior alone explains motivation or causality.
What is Product analytics?
Product analytics is the collection and analysis of behavioral data to understand how users experience a digital product and how that experience affects outcomes.
Why it matters
It uses events, properties, profiles, funnels, paths, cohorts, retention, experiments, and qualitative feedback to answer questions about activation, feature adoption, friction, engagement, and value. Good product analytics begins with decisions and a governed tracking plan. It combines descriptive analysis with research and experimentation rather than assuming behavior alone explains motivation or causality.
Example
A team analyzes which onboarding actions predict long-term retention, then tests a redesigned flow that encourages those actions.