Definition
Event Tracking
Event tracking is the practice of recording discrete user actions - signup completed, report exported, checkout finished - as structured data: an event name, a timestamp, a user identity, and properties describing context. It is the raw material of all product analytics; every funnel, cohort, and retention curve is a query over tracked events.
Interactive diagram - hover the elements. Plotted values are illustrative examples, not measurements.
How are events actually captured?
Four routes: client SDKs (richest context, subject to blockers), server-side tracking (authoritative for business events like payments), tag managers such as GTM (fast to deploy against an existing dataLayer), and autocapture (records interactions wholesale for retroactive definition). Mature setups combine them deliberately - server-side for money events, client-side for behavior - rather than picking a religion.
What makes event data trustworthy?
Three disciplines: one naming convention enforced mechanically (Object-Action casing agreed once), properties typed and validated at the pipeline edge, and QA that checks events against the tracking plan on every release. Trust erodes through small unnoticed breaks - the release that renamed an event, the property that became a string - which is why governance beats heroic cleanup.
Example event: name 'Report Exported', properties {format: "pdf", pages: 12, plan: "growth"}, fired server-side on export completion - one row in the tracking plan, one building block for a dozen analyses.
In practice: Event tracking done right the first time is the whole promise of our implementation sprint.
Event Tracking: common questions
How many events should a product track?+
Fewer than teams expect: a focused product surface usually needs tens of well-chosen events, not hundreds. Every event should answer a named question; with event-based pricing, unowned events are literally money.
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