Product Analytics and User Journeys

What is product analytics?

Product analytics examines how people use a digital product to understand journeys and identify friction.

Common tools: Google Analytics 4, Mixpanel, Amplitude, PostHog.

Events and properties

Good event-tracking practice:

• Use a consistent naming convention (e.g., object_action: cart_added, lesson_started)
• Maintain a tracking plan: a document listing every event, its properties, and when it fires
• Avoid collecting personal information that isn't needed for the analysis

Funnels and cohorts

Comparing cohorts shows whether a product change is associated with different activation or retention. Proving cause usually requires an experiment.

Example

Registration funnel:

The profile step has the biggest drop. Investigate:

• Is the form asking for unnecessary information?
• Do errors occur on specific devices or browsers?
• Is the step slow to load?

The drop-off identifies a problem area, not necessarily its cause. User research or an A/B test can confirm the cause.

Common mistakes

• Inconsistent event definitions: if one team logs lesson_viewed on page load and another after 30 seconds of engagement, the metrics aren't comparable.
• Tracking everything without a plan, producing noisy, unusable data.
• Changing event names without documenting it, which breaks trends.
• Over-relying on averages when a few power users dominate.

Try it: Map the key events for a learner who discovers a course, signs up, starts a lesson, and completes it. Name one metric for each stage.