Chan Kang | The Slashie

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Google Analytics 4 Dimensions: Complete Guide (GA Episode 2)

ga4-dimensions

What is Dimensions in Google Analytics?

In Google Analytics, a dimension is an attribute that describes your data, such as page URL, traffic source, device type, or country. Dimensions tell you what or who is being measured, and they work together with metrics (numbers) to help you understand user behavior.

Why Are Dimensions Important?

Dimensions help you better understand your data by adding context to the numbers. They allow you to uncover insights, such as who your users are, where they come from, and how they interact with your site, that you wouldn’t get from metrics alone.

Examples of Dimensions in Google Analytics:

Common dimensions in Google Analytics include:

  • Device category: The type of device used, such as desktop, mobile, or tablet.

  • Source / medium: Where the visit came from, like Facebook (source) and email (medium).

  • Browser: The browser used to access your site, such as Chrome or Safari.

  • Country: The user’s geographical location, for example, the United States.

  • Language: The language set on the user’s browser or device, such as English.

  • Campaign / Campaign ID: The marketing campaign that drove the visit or conversion, e.g. Spring2025_Sale.

  • Page location: The URL of the page the user visited, such as https://www.yourwebsite.com/blog/how-to-train-a-puppy.

  • Custom dimensions: User-defined attributes created to track specific information unique to your business. (The dimensions you create yourself to track specific information about your users)

Dimension vs Metric: What’s the Difference?

Metrics are quantitative measurements. They show how many or how much by using numbers, such as page views, sessions, or conversions.

Dimensions are qualitative attributes. They describe who, what, where, when, or why the activity happened, such as device type, traffic source, or page URL.

In short, dimensions describe the data, while metrics measure it: metrics quantify the dimension values.

Types of Dimensions in Details

Types of Dimensions in Google Analytics 4 (GA4)

In GA4, dimensions generally fall into two main types: predefined dimensions and custom dimensions.

  • Predefined dimensions are built into GA4 and available right away in reports and Explorations.

  • Custom dimensions are created by you to track business-specific information that GA4 doesn’t collect by default.

Below are the main groups of predefined dimensions, ordered from most important for beginners to more advanced or niche use cases.

1. Traffic Source

Shows where users come from, such as organic search, paid ads, social media, or referrals.

2. Page / Screen

Describes what content users view, including page URLs, page titles, or app screens.

3. Platform / Device

Explains how users access your site or app, such as device type, browser, and operating system.

4. Geography

Shows where users are located, including country, region, and city.

5. User

Describes user-related attributes, such as new vs returning users or user status.

6. Event

Provides details about user interactions, such as event names, conversion status, and event values. An event is a user interaction on the site. It can be a scroll, a click, a view, etc.

7. Time

Breaks data down by date and time, helping you analyze trends over specific periods.

8. Attribution

Explains how different channels contribute to conversions across the user journey.

9. Session-Scoped

Focuses on session-level information, like the source or campaign that started a session.

10. User-Scoped

Captures first-touch information, such as the user’s first source or first campaign.

11. Demographics

Includes user attributes like age, gender, and interests (availability depends on consent and region).

12. Ecommerce

Tracks online shopping activity, including products, transactions, and promotions.

13. Google Ads

Contains dimensions related to Google Ads campaigns, such as ad group and keyword (when Google Ads & GA4 linked).

14. Search Ads 360

Includes dimensions specific to Search Ads 360, mainly for enterprise users.

15. Video

Covers interactions with video content, such as video title or provider.

16. Link

Tracks outbound link clicks and related link attributes.

17. User Lifetime

Focuses on long-term user value, such as lifetime revenue and engagement.

18. Publisher

Relates to ad monetization, including ad formats and ad sources (used mainly by publishers).

19. Gaming

Used for game apps, tracking in-game events, levels, and achievements.

20. General

Includes miscellaneous dimensions that don’t fit neatly into other categories, such as file informations, search terms.

What are Custom Dimensions

Custom dimensions are user-defined attributes that you set up in GA4 to track information that isn’t collected automatically. They let you measure details unique to your business, such as membership level, content type, or author name.

Because every business has different goals, custom dimensions help fill data gaps and enable more personalized reporting. 

That said, they’re optional—if GA4’s built-in dimensions already meet your needs, adding custom dimensions may not provide extra value.

GA4 Event Note:

Every GA4 event includes parameters, which are pieces of information that add context to the event or user. For example, a click event may include parameters such as the clicked URL or the link’s location on the page.

When you register event parameters or user properties as custom dimensions, they become available as dimensions in GA4 reports and Explorations.

Use cases for custom dimensions:

  • Content type: Track whether a page is a blog post, landing page, or documentation page.

  • Author name: Analyze performance by content author.

  • Membership level: Compare behavior between free and paid users.

  • Logged-in status: See differences between logged-in and anonymous users.

  • Form location: Identify which page or section drives form submissions.

  • User role or account type: Understand how different user groups use your product.

  • Product category (custom): Add extra classification beyond default ecommerce dimensions.

Step by Step Guide

How to Add Custom Dimensions in Google Analytics 4

Before you can use custom dimensions in GA4 reports, you must create them first. Keep in mind that custom dimensions are not retroactive, GA4 only collects data from the moment they’re set up, not from past events.

The setup process depends on the scope of the dimension you’re creating:

  • Event-scoped (most common)

  • User-scoped

  • Item-scoped (for ecommerce)

Step 1: Send the Data to GA4

Custom dimensions are based on event parameters or user properties.

For example, a form submission event may include a parameter like form_location = landing_page.

You can send these parameters to GA4 in two ways:

  • Google Tag Manager (recommended) – more flexible

  • GA4 Admin → Events – simpler, but limited

In most cases, Google Tag Manager is better option.

Step 2: Configure the Event in Google Tag Manager

Log in to Google Tag Manager, enable the required variables, and configure your event and its parameters.

Once the event is firing correctly, you’re ready to register the parameter as a custom dimension.

Step 3: Create the Custom Dimension in GA4

Go to Admin → Custom definitions → Create custom dimension, then fill in:

  • Dimension name: A clear, readable name (e.g., Form location)

  • Scope: Select Event, User, or Item, depending on your setup

  • Description (optional): Helpful for documentation, but not required

  • Event parameter: Enter the exact parameter name sent from GTM (must match exactly)

Click Save when finished.

Step 4: Wait for Data to Appear

The custom dimension will usually become available in GA4 reports and Explorations within 24–48 hours, once new data is collected.

Key Things to Remember for
Effective Custom Dimension Implementation

  • Custom dimensions only work after setup: GA4 does not apply them retroactively, so historical data is not available.

  • Match parameter names exactly: Parameter names are case-sensitive and must match what’s sent to GA4.

  • Use Google Tag Manager when possible: GTM makes tracking easier to manage, scale, and debug.

  • Align with business goals: Only create custom dimensions that support clear reporting or decision-making needs.

  • Use meaningful values: Ensure the data collected is clear, consistent, and easy to interpret.

  • Avoid high-cardinality dimensions: Too many unique values (like full URLs or timestamps) can limit reporting usefulness.

  • Follow consistent naming conventions: Use clear, standardized names to keep your GA4 property organized.

  • Prevent data duplication: Don’t track the same information in multiple dimensions or scopes unless there’s a clear reason.

FAQs

What Is a Primary Dimension in Google Analytics?

A primary dimension is the main attribute used to organize data in a Google Analytics report. It determines how rows in a table are grouped, such as by page, source, or device type.

What Is a Secondary Dimension in Google Analytics?

A secondary dimension adds extra context to the primary dimension by layering in another attribute. It lets you analyze the same data from an additional angle, such as viewing page performance by traffic source or device.

Source vs Medium: What’s the Difference

Source tells you where the traffic comes from (e.g., Google, Facebook), while Medium explains how the traffic arrived (e.g., organic, cpc, email). Together, source and medium show both the origin and the type of traffic.

What Is Scope in GA4?

Scope defines how long a piece of data applies and what level it’s associated with—such as a user, session, event, or item.

User-scoped data applies to a user across all visits and sessions, like first traffic source or membership type.

Session-scoped data applies only to a single visit (session), such as the source or campaign that started that session.

Event-scoped data applies only to a specific action, like a button click or form submission.

Item-scoped data is used for ecommerce and applies to individual products, such as product category or item brand.

Choosing the correct scope ensures your data is accurate and prevents reporting errors or misleading insights.

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