Module
Module 3 of 6Lesson 1 of 3~17 min

Events, properties and naming convention

Poorly named or overly granular events produce data nobody dares to use anymore. This lesson helps a PM turn a user journey into events and properties at the right level of detail, then settle on a naming convention the whole team shares. It is the foundation of a tracking plan engineers can implement without back-and-forth.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to describe a flow as events and properties, choose the right level of detail, and write a naming convention the whole team applies.

Topics covered

  • analytics events
  • event properties
  • user properties
  • naming convention

Where it fits

Design the tracking plan

Which events should I collect, how should I name them and who should they be attached to, so that the data answers my questions?

Lessons in this module

  1. Events, properties and naming convention (this lesson)
  2. Identity, accounts and event sources
  3. Write the tracking plan and the acceptance criteria

What you will learn in the course

This lesson is part of the course Instrument a product and use data to make decisions

  • Build a product's metrics tree (North Star, input metrics, guardrails) from the decisions to be made, and rule out vanity metrics.
  • Design an implementable tracking plan (events, properties, naming convention, identity and accounts, emitting source, owners).
  • QA and monitor event collection to get reliable data, and know what to do when it is not.
  • Collect usage data in line with the GDPR and the CNIL rules (consent, audience measurement exemption, minimisation, retention period).
  • Analyse a conversion funnel, activation and cohort retention, and interpret the resulting curves correctly.
  • Choose a product analytics tool (PostHog, Amplitude, Mixpanel, GA4, data warehouse) based on needs, constraints and cost.
  • Turn an analysis into a reasoned decision (dashboard, decision memo) while avoiding interpretation traps (vanity, Simpson, correlation, small counts).

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