Product analytics guide
Product analytics: tools, events, and dashboards for PMs
Product analytics is the collection and analysis of user behavior data to understand how people use your product — and to make informed decisions about what to build, fix, or change.
Analytics without action is just data hoarding. The goal is to generate decisions — not dashboards.
The analytics stack
Most product teams use several tools together. Each layer answers a different question.
Record every user action so you can query, segment, and visualize behavior patterns.
Traffic sources, page views, and acquisition funnels. The entry point for most teams.
Watch real users navigate your product — see where they click, scroll, and get stuck.
Build reports for stakeholders. Combine product data with revenue, support, and growth data.
Run controlled experiments to measure the causal impact of product changes.
Event taxonomy
An event is any user action you track. Good event design is everything — bad taxonomy creates garbage data that nobody trusts.
Naming convention
Examples: user_signed_up, feature_clicked, checkout_completed. Lowercase, underscores, object first.
Always track these events
user_signed_uponboarding_completedkey_feature_usedsubscription_startedsubscription_cancelledFunnels
A funnel shows how many users complete each step of a sequence. Funnel analysis reveals where users drop off — that drop-off point is your biggest product opportunity.
Example funnel: signup flow
Visit homepage
Start signup
Complete email
Verify email
Complete onboarding
Use core feature
Cohort analysis
A cohort is a group of users who share a characteristic — usually sign-up date. Cohort retention tracks what percentage of each cohort is still active one, two, and three months later.
If later cohorts retain better than earlier ones → your product is improving.
If all cohorts flatten at the same retention rate → you have hit your natural retention ceiling. Acquisition growth will not save you — the product needs to improve.
The PM analytics workflow
Analytics is a habit, not a project. Here is how data-driven PMs structure their review cadence.
Check your North Star metric dashboard — any anomalies?
Review funnel conversion — any step getting worse?
Cohort retention trend — is retention improving over time?
Full product health report for leadership.
Next steps
Learn data skills for your role
Analytics fluency is table stakes for PMs and data analysts alike. Explore the role tracks to build the full skillset.