GA4 architecture

GA4 is built on an event model. Every user interaction is an event with parameters:

event_name: "purchase"
parameters:
  transaction_id: "T123"
  value: 99.90
  currency: "USD"
  items: [{item_id: "SKU123", item_name: "...", quantity: 1, price: 99.90}]

Unlike Universal Analytics, GA4 has no special page-view hit. page_view is simply an event like any other.

Key concepts

Concept GA4 Universal Analytics (retired)
Unit of data Event Hit (pageview, event, transaction)
Identifier User-ID + Client-ID + ML modelling Client-ID (cookie)
Funnels Explorations → funnel report Goals (fixed)
Sampling None when integrated with BigQuery Applied on high traffic
Web + app One property Separate accounts

E-commerce in GA4

GA4 ships with a built-in event schema for e-commerce. The essential events:

view_item        — a PDP view
add_to_cart      — adding to the cart
begin_checkout   — starting checkout
purchase         — a completed purchase

Additional events for extended analytics:

view_item_list   — products shown in a listing
select_item      — a click on a product
view_promotion   — a banner or promotion shown
select_promotion — a click on a banner

Correctly implemented GA4 e-commerce tracking gives you the purchase funnel, product reports, promotion performance and traffic source reporting out of the box.

Tip: if you run a personalization platform — recommendations, popups — make sure view_promotion and select_promotion fire when widgets are shown and clicked. That is what lets you attribute their contribution to revenue inside GA4.

The limits of GA4

GA4 does not replace specialised analytical tools:
– For product analytics (Amplitude, Mixpanel), GA4 is less flexible in ad-hoc segmentation
– For A/B testing, GA4 is an observation tool, not a decision-making one
– For technical diagnostics — latency, error rates — you need an APM, not GA4

GA4 is the standard for marketing analytics, attribution and SEO. For product analytics and experimentation it is used alongside specialised tools.