What Is a Dimension in Google Analytics? Definition and Examples

Google Analytics is like a window into your web site, revealing insights that may enhance your advertising and conversion charges. When you first log in to Analytics, it may really feel like getting into a big library filled with foreign-language books, particularly in Google’s new model of the software program, GA4.

Fortunately, when you perceive the essential framework that underpins Google Analytics, it’s a lot simpler to make use of. This construction revolves round two elementary knowledge classes: metrics and dimensions. While metrics—quantifiable values that fluctuate—are usually easy, Google Analytics’ notion of dimensions calls for a contact extra perception. 

Here’s what you might want to learn about dimensions in Google Analytics.

What are dimensions in Google Analytics?

In Google Analytics, dimensions are attributes that allow you to categorize your web site guests, classes, and interactions. They allow you to analyze knowledge by dividing it into distinct classes. 

Dimensions work alongside metrics, that are numeric representations of consumer habits like pageviews, bounce charges, and session durations. Dimensions add context to metrics, revealing insights into your website’s efficiency and consumer actions.

Combining dimensions and metrics allows you to craft exact reviews and scrutinize viewers segments, revealing patterns, alternatives, and areas to refine your digital technique. In Google Analytics, dimensions have inexperienced labels, whereas metrics have blue labels. 

How do Google Analytics dimensions work?

Most Google Analytics reviews are organized as tables or charts with the X metric segmented by the Y dimension. For instance:

• “Users” (metric) by “Age” (dimension)
• “Transactions” (metric) by “Country” (dimension)
• “Sessions” (metric) by “Source” (dimension)
• “Add to carts” (metric) by “Product Name” (dimension)

Some dimensions have prescribed choices. For instance, Google Analytics has a preset checklist of nations it refers to for its “country” dimension. Other dimensions, corresponding to “product,” might be outlined by no matter web site knowledge you present. If you’re on Shopify, the native Google Analytics 4 (GA4) integration robotically populates Google Analytics along with your retailer’s product knowledge.

There are over 170 normal dimensions in GA4. Most companies don’t want all of them. For instance, there’s a set of dimensions associated to ecommerce (together with “ecommerce purchase ID,” which lets you observe particular person buy transactions, and “product SKU,” which may also help you perceive which merchandise are promoting nicely and which of them may have extra promotion) and one other set associated to gaming (together with “level name,” to trace consumer progress inside totally different ranges, and “game version,” which lets you monitor consumer exercise in totally different variations or updates). It’s unlikely a web site wants each. 

Advanced customers also can create as much as 25 Google Analytics customized dimensions to seize knowledge that’s not robotically tracked, corresponding to a dimension indicating whether or not a buy is one-time or recurring. However, in keeping with Google’s privateness coverage, dimensions can’t embody personally identifiable data (PII), like names, emails, or cellphone numbers.

Types of dimensions in Google Analytics

1. User scope
2. Session scope
3. Item (product) scope
4. Event scope

Google Analytics classifies dimensions primarily based on the corresponding metric varieties, ensuing in 4 distinct classes of dimensions. (These classes align with the 4 sorts of metrics.) The metric sort to which a dimension is linked determines its scope—primarily, the vary of metrics to which these dimensions are relevant.

Here are the 4 dimensions varieties and a few widespread examples for every:

1. User scope

User-scoped dimensions are properties of a person consumer, separate from the actions the consumer takes on the web site. User-scoped dimensions usually stay constant all through their complete session on a web site.

Examples of normal user-scoped dimensions embody:

• First session date. The date on which the consumer first visited the web site.
• Age. ​The consumer’s age by bracket; both “18-24,” “25-34,” “35-44,” “45-54,” “55-64,” or “65+.”
• Last lively date. The date on which the consumer most not too long ago engaged with the web site.

2. Session scope

A Session is a person go to to a web site by a consumer, together with all of their exercise in the course of the go to. If a consumer visits a web site twice in one week, that week has one “User” and two “Sessions.” Session-scoped dimensions are the properties associated to the go to.

Examples of session-scoped dimensions embody:

• Session supply. The web site that referred the customer to your web site. This might be expressed as a web site (e.g., “facebook.com”) or a supply sort (e.g., “email”).
• Session period. The time a consumer spends visiting the web site earlier than leaving, expressed in minutes and seconds.
• Device class. The machine sort on which the consumer visited the location (e.g., “Desktop,” “Tablet,” or “Mobile.”)

3. Item (product) scope

Item-scoped dimensions are properties hooked up to a person services or products on the market on a web site. In the earlier model of Google Analytics (Universal Analytics), these have been known as product-scoped dimensions, referring to ecommerce merchandise. In GA4, that definition was widened to “items” to use to each merchandise and companies. This set of dimensions is integral for conducting e-commerce evaluation.

Examples of normal item-scoped dimensions embody:

• Item identify. The identify of the services or products.
• Currency. The forex the services or products is offered in. 
• Item model. The model of the services or products (related for shops that promote a number of manufacturers).

4. Event scope 

Event-scoped dimensions are for properties associated to something aside from a consumer, session, or merchandise. Examples of occasions are pageviews, kind submissions, and scrolls.

Examples of normal event-scoped dimensions embody:

• Page title. The web page’s identify from a pageview.
• Percent scrolled. How far down a web page a consumer scrolls. This is tied to an automated occasion known as “Scroll” that triggers repeatedly as a consumer strikes down a web page. For instance, 90% scrolled means the consumer has scrolled via 90% of the web page displayed on their machine.
• Hour. The hour of the day in which any occasion occurred. For instance, an occasion at 9 a.m. has a worth of 9. 

How to make use of dimensions in Google Analytics

1. Add secondary dimensions to reviews
2. Create customized reviews
3. Create customized dimensions

Once you perceive the basics of dimensions, you may transcend a normal Google Analytics report to create new insights for your enterprise. Here’s how:

1. Add secondary dimensions to reviews

GA4 comes with a number of pre-made reviews for web site managers. Once you perceive dimensions, you may customise them to suit your context. 

Most reviews begin with a single main dimension and a number of metrics. For instance, under is a portion of one among GA4’s hottest reviews, the Traffic acquisition report, which organizes the “Users,” “Sessions,” and “Conversions” metrics (not pictured) by the “Session” dimension default channel group. 

This instance website, which sells flooring merchandise, receives important site visitors from natural search outcomes. As a marketer, chances are you’ll need to perceive which webpage customers are touchdown on when coming from these sources. You can be taught this by clicking the blue “+” icon (seen in the screenshot above) and choosing “Landing page” as a secondary dimension. This provides a second layer of segmentation to the report, exhibiting the commonest mixtures of “Session default channel group” and “Landing page + query string” for a “User“ or “Session.” 

This extra custom-made report reveals what merchandise and pages have been essentially the most profitable in bringing in customers, which in flip might assist refine the corporate’s search engine optimisation, advertising, and product methods.

2. Create customized reviews

GA4 has a sturdy Explorations software for creating your reviews, which may also help you create numerous metric and dimension mixtures, plus a number of choices to visualise them:

GA4 customers can use the Template gallery to pick out preset reviews; skilled customers can construct templates from scratch by choosing “Blank” and selecting their mixtures of metrics, dimensions, and visualizations from scratch. Examples of customized reviews helpful for ecommerce shops embody:

• Add gadgets to cart (metric) by Item identify (dimension)
• Item income (metric) by Currency (dimension)
• Purchases (metric) by Item model (dimension)

3. Create customized dimensions

You can transcend GA4’s current setup by including customized knowledge particular to your enterprise. Creating customized dimensions is easy: go to the Admin part of your Google Analytics account and discover “Custom Dimensions” subsequent to “Custom Metrics” beneath “Custom Definitions.” Ensure you outline the right sort of dimension.

Examples of customized dimensions that may be useful to ecommerce corporations embody:

Collection filter sort

This may also help you observe clicks to your retailer’s buying filters and use a customized dimension to outline the filter sort, corresponding to worth or dimension. This knowledge can inform future assortment web page UX selections by exhibiting what filters matter most to your customers. For instance, if most customers make use of filters for coloration, you can strive enhancing their buying expertise by providing coloration choices subsequent to your product photographs.

Item/Product dimension

If you promote attire and your product comes in totally different sizes, including a customized dimension worth for dimension may also help you run reviews and anticipate future stockouts or reorders.

Form submission sort

Many shops have a multipurpose contact kind with choices to achieve out about product help, wholesale orders, or different particular use instances. By monitoring kind submissions and including a customized dimension primarily based on the kind of submissions, you may acquire extra perception into whether or not your kind submissions are marketing-, sales-, or support-based.