Quickstart stack

A Google-native stack: GA4 and BigQuery at the center

The most common shape among the stacks people draw in Stack Builder: Tag Manager into GA4, GA4 exported to BigQuery, Looker reporting from the warehouse, and audiences sent from BigQuery to the ad platforms.

Open this stack in Stack Builder → No sign-up. It opens on the canvas, ready to change.

8 tools · 10 connections

Scroll sideways to see the whole stack. Arrows show the direction data moves. Every connection is listed by name below.

What it is for

Teams that already run on Google Analytics and Google Ads end up here, because each step is a native export rather than an integration project. It is a good default for a marketing team that wants its own data in a warehouse without buying a CDP.

It includes the edge most diagrams forget: cost and conversion data imported from Google Ads back into BigQuery, so spend and outcomes sit in the same place as the behavior data.

Why each tool is here

OneTrust Consent Management

Consent management. It records what each visitor agreed to and passes that state on, so the tools downstream only collect and use what they are allowed to. Here it sets Consent Mode for Tag Manager and GA4.
Google Tag Manager Tag Management

Tag management. Fires the GA4 tags on the site.
Google Analytics 4 Analytics & BI

Web analytics, and the collection point: its daily export is how raw events reach the warehouse.
BigQuery Data Warehouse

The warehouse. GA4 events, the raw archive and ad cost data meet here, and audiences are built here.
Google Cloud Storage Cloud Storage

Cheap storage for the raw event archive, loaded into BigQuery as external tables.
Looker Analytics & BI

Reporting on top of BigQuery, through a semantic model refreshed hourly.
Google Ads Advertising

Paid search. Receives Customer Match audiences and sends cost and conversion data back.
Meta Ads Advertising

Paid social. Receives audiences built in BigQuery.

How data flows

Tag Manager streams pageviews into GA4, with OneTrust setting consent on both. Once a day GA4 exports to BigQuery and archives raw events to Cloud Storage, which BigQuery reads as an external table.

From BigQuery, Looker refreshes hourly, and Customer Match and Meta audiences go out daily. Google Ads sends cost and conversion data back to BigQuery daily.

Every connection

OneTrust to Google Tag Manager Consent mode · Real time, on each event
OneTrust to Google Analytics 4 Consent state · Real time, on each event
Google Tag Manager to Google Analytics 4 Tagged pageviews · Streaming, continuously
Google Analytics 4 to BigQuery BigQuery Export · Batch, daily
Google Analytics 4 to Google Cloud Storage Raw event archive · Batch, daily
Google Cloud Storage to BigQuery External table load · Batch, daily
BigQuery to Looker Semantic model refresh · Batch, hourly
BigQuery to Google Ads Customer Match · Batch, daily
BigQuery to Meta Ads CAPI audiences · Batch, daily
Google Ads to BigQuery Cost & conversion import · Batch, daily

When this is the wrong choice

You need customer profiles that update during a session. Everything after GA4 here runs daily or hourly.
Your company standardized on another cloud. The native exports are the point; on Azure or AWS look at the Microsoft / Azure quickstart.
You need email or app messaging. This stack has no engagement tool; add one, or start from Ecommerce & Retention.

Other quickstart stacks

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