Google Analytics 4 Complete Guide

Overview

Google Analytics 4 (GA4) is Google's event-based analytics platform for measuring user interactions across websites and applications. Every user interaction is tracked as an event with associated parameters, providing flexible cross-platform measurement.

When to Use This Skill

Invoke this skill for any GA4-related task:

• Setting up GA4 properties, data streams, and Measurement IDs

• Installing GA4 via gtag.js, GTM, or CMS plugins

• Implementing event tracking (automatic, recommended, custom, ecommerce)

• Creating custom dimensions, audiences, and reports

• Exporting data to BigQuery for SQL analysis

• Server-side tracking via Measurement Protocol

• User ID and cross-device tracking

• Privacy compliance, Consent Mode, and GDPR/CCPA

• Testing and debugging with DebugView

Quick Start

• Create property: analytics.google.com -> Admin -> Create -> Property

• Create data stream: Add web stream, note Measurement ID (G-XXXXXXXXXX)

• Install tracking (choose one):

• GTM (recommended): Install container, create Google Tag with Measurement ID, trigger on All Pages, publish

• gtag.js direct: <script async src="https://www.googletagmanager.com/gtag/js?id=G-XXXXXXXXXX">&#x3C;/script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-XXXXXXXXXX'); </script>

• Verify: Enable GA Debugger extension, check Admin -> DebugView for session_start, page_view

• Send custom events: gtag('event', 'button_click', { button_name: 'Subscribe', button_location: 'header' });

Decision Tree: Which Reference Do I Need?

What are you trying to do?

Setting up GA4 for the first time? -> references/setup.md Understanding how events work? -> references/events-fundamentals.md Implementing standard tracking events? -> references/recommended-events.md Creating business-specific custom events? -> references/custom-events.md Making parameters appear in reports? -> references/custom-dimensions.md Implementing User ID / cross-device? -> references/user-tracking.md Building audiences for remarketing? -> references/audiences.md Analysing data in GA4 reports? -> references/reporting.md Exporting to BigQuery for SQL analysis? -> references/bigquery.md Installing via gtag.js directly? -> references/gtag.md Setting up GA4 in Google Tag Manager? -> references/gtm-integration.md Sending events from server/backend? -> references/measurement-protocol.md Testing and debugging implementation? -> references/debugview.md Implementing GDPR/Consent Mode? -> references/privacy.md Configuring Admin settings? -> references/data-management.md

Core Concepts

Event-Based Model

GA4 tracks everything as events in four categories:

Category Description Examples

Automatic Fire without configuration session_start, first_visit

Enhanced Measurement Toggle on/off in settings scroll, click, file_download

Recommended Google-defined with standard parameters purchase, login, sign_up

Custom Business-specific tracking demo_requested, trial_started

Key Limits

Limit Value

Event names per property 500 distinct

Parameters per event 25

Event name length 40 characters

Parameter name/value length 40 / 100 characters

Custom dimensions (event/user/item) 50 / 25 / 10

Audiences per property 100

Measurement ID

• Format: G-XXXXXXXXXX (G- prefix + 10 alphanumeric characters)

• Location: Admin -> Data Streams -> Web Stream

• Used in: gtag.js config, GTM tags, Measurement Protocol

Common Workflows

Ecommerce Tracking

• Review recommended events for the purchase funnel: view_item -> add_to_cart -> begin_checkout -> purchase

• Structure items array (required: item_id OR item_name; recommended: price, quantity, item_category)

• Test with DebugView, then register custom item parameters as custom dimensions

Cross-Device Tracking

• Implement User ID and configure Reporting Identity (Admin -> Data Settings)

• Set user properties and build cross-device audiences

GDPR Compliance

• Set up Consent Mode with default denied state

• Integrate with CMP (OneTrust, Cookiebot, etc.), update consent on user acceptance

• Test consent implementation with DebugView

Custom Reports

• Understand available data in reporting

• Register custom parameters as dimensions, create Explorations

• For unsampled data, export to BigQuery

Best Practices

• Naming: Use snake_case, be descriptive and action-oriented, keep under 40 characters, avoid generic names

• Implementation order: Enhanced Measurement -> recommended events -> custom events -> custom dimensions

• Data quality: Separate test/production properties, set up internal traffic filters from day one, document all custom events, audit regularly with DebugView, export to BigQuery for backup