Event Taxonomy

An event taxonomy defines the rules for naming events, categorizing them, specifying required and optional properties, and documenting their purpose. Good taxonomies use consistent patterns like object-action naming (e.g., button_clicked, form_submitted) and standardize property names across all events.

For growth teams, a well-designed event taxonomy is the difference between a data asset that enables self-serve analysis and a chaotic data swamp that requires tribal knowledge to navigate. AI and machine learning pipelines are particularly sensitive to taxonomy quality because inconsistent event names and properties create noisy features that degrade model performance. Growth engineers should invest in taxonomy design before implementing tracking, treating it as a shared contract between product, engineering, data science, and marketing teams. Key design principles include using a consistent naming convention, documenting every event with its purpose and expected properties, versioning the taxonomy to manage changes, and implementing validation that rejects events not conforming to the schema. Teams should assign taxonomy ownership to prevent drift and conduct regular audits to identify undocumented events, deprecated tracking, and naming inconsistencies.