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Research methodCraft conventionIntermediate

Product Analytics

Measuring what people do at scale, which tells you where problems are and never why they exist.

Definition

Product analytics records user actions as events and aggregates them. It is comprehensive about behaviour within the product and silent about intention, context and everything that happens outside it.

Craft convention. True because the industry converged on it. Breaking it costs familiarity, not correctness.

On this page
  1. Definition
  2. What analytics can and cannot answer
  3. Practical rules
  4. Continue from here

What analytics can and cannot answer

  • Can: how many, how often, in what order, where people stop.
  • Can: whether a change moved a number.
  • Cannot: why people stopped.
  • Cannot: what people wanted and did not find.
  • Cannot: who never arrived at all.

Practical rules

  • Design the event taxonomy before instrumenting. Renaming events after the fact loses history.
  • Segment before concluding. An aggregate median usually hides two distinct populations.
  • Watch for survivorship bias: everyone in your data is someone who got that far.
  • Pair every surprising number with qualitative work before acting on it.
  • Respect consent and data minimisation obligations. Collect what you will use.

Continue from here

Each link says what the connection is, so you can tell a principle from an alternative from a thing people mix this up with.

Applies when you are designing

A DashboardA Data TableA Search ExperienceAn AI ProductAn Ecommerce ExperienceAn Enterprise WorkflowAn Onboarding FlowAuthenticationSettings

Principles behind this

The reasoning this solution is an application of.

Often used with

These usually appear in the same screen or the same decision.

Short definition

The one-paragraph version, for when that is all you need.

Related concept

Connected closely enough to change how you apply this.