Analytics tracking and dashboards expert

It is the plan for what you measure and how: the events, their properties, naming rules, conversion definitions and the tools that collect them. A good one means web, app and CRM data use the same definitions, so a sign-up counts once and means the same thing in every report.

A list of events and properties, a naming convention, the conversions that matter and their definitions, an owner for each event, and a test for each one. It should also say which tool holds which data. At Topship, the conversions were sign-ups, quotes and completed orders.

Each gets its own set-up with shared definitions. At Topship, GA4 and Google Tag Manager covered three web domains, and the apps got Firebase and their own GA4 property. Sharing definitions for sign-ups and orders is what lets web and app results be read side by side.

One that answers the decision the team makes most often, usually channel results against an outcome such as sign-ups or revenue. Every number needs a definition and an owner. State what the data leaves out: the Syllabus.ng CRM dashboard undercounts sends because inactive contacts are deleted each quarter.

Tracking records what happened: the events, sources and conversions. Attribution decides which channel gets credit for them. Attribution is only as good as the tracking under it, so I fix the tracking plan first. At Ecobank, the attribution pipeline I built ran from acquisition to activation.