Using secondary dimensions, segments in Google Analytics

In this article, we’re going to cover the use of secondary dimensions and segments in GA.

Secondary dimensions

What are secondary dimensions?

To answer that question we need to understand what primary dimensions are. A quick explanation as to what a primary dimension or just dimension is: “an attribute or a characteristic that describes an object that can be given values.”

These are used to segment, sort and organise data. Examples being:

Browser type (Chrome, Firefox)
Country
Campaign
Medium
Language
Device category

GA reports come with default primary dimension that displays certain metrics in relation to the dimensions.

Now, a secondary dimension is a feature that allows you to define the primary dimension and add the secondary dimension column to the same table of data. This puts your data into a deeper context than a basic primary dimension level.

How to use secondary dimensions?

You can use them in many different ways.

In your Google Analytics reporting tab, a standard report will display your landing page with metrics for acquisition, behaviour, and conversions.

Behaviour => Site content => Landing pages

To get the source of that traffic to the landing page you then add a secondary dimension: Source/medium to the same reporting view to get a clear view of the source of your traffic.

Using secondary dimensions, segments in Google Analytics

Once you add a secondary dimension, it broadens your view of data and allows you to drill down to the most important aspect of the information you may need. As shown above you can use the search pane to display particular pages or source/mediums. This can create a better understanding of user traffic and identify patterns. The last arrow points you to the goals. This gives you an in-depth look at a particular goal. To wrap it all up, using secondary dimensions with all these other tools enlarges your view allowing you to get a better in-depth understanding of your analytics data. Most professionals rarely look at their analytical data without the use of secondary dimensions.

There are many combinations you can use to visualise data in your reports. Some of these can be used interchangeably. For instance, the above example can be set up as follows to view the data in another angle:

Traffic source => all traffic => source/medium(primary dimension) + landing page (secondary dimension)

To know which secondary dimensions to use, you have to have a question in mind before you open your Google Analytics. The question will define which dimensions to use in your report. Let's say you want to know where the types of visitors behaviour by city. The following report will be of use:

Audience => behaviour => new vs returning => visitor type (primary dimension) + city (secondary dimension)

Secondary dimensions give more meaning to your data by adding context to your data.

Segments

What is a segment?

A segment is created using one or more filters that do not alter the underlying data. Those filters isolate sections of data on three-segment levels which are users, sessions and hits. Segments allow for a drill down on your analytics data to extract deeper insights.

The three-segment levels can be explained as follows:

User: The people visiting your website (NB: user segments can only apply for a maximum of three months)
Session: Website interactions by a single person grouped into what Google Analytics sessions
Hit: Site interactions during a session. These are lower level. Usually visiting a certain page or performing a certain event

Using segments

You can build your reports and apply segments to focus on a certain type of user or session. A maximum of four segments can be applied at a time. This does allow you to compare your data on a side by side view.

Google Analytics offers predefined segments that you can use for your reports. These predefined segments can be edited creating new segments that suit your reporting needs. You can also use these segments to build audiences for Google Ads marketing. If the predefined segments don't suit your needs, you can create custom segments from scratch.

When creating segments, you use dimensions and metrics in your analytics reports.

There are two types of segments.

Let's take a look at simple segments:

Demographics: Using demographic information to create a segment
Technology: Using the technology of the users to create a segment. This includes mobile device type and browser type
Behaviour: Creating a segment of your users by visiting and transacting pattens
Date of first session: Segmenting your users when they first visited your site
Traffic sources: Segmenting your users by how they got to your site
Enhanced e-commerce: Creating segments of your users using their shopping behavior

Advanced segments:

Conditions: Creating a segment of your users according to how they fit into a certain condition or criteria
Sequences: Creating a segment of your users by how they all committed a series of events in a sequence

Examples:

Traffic sources – medium: contains organic
Advanced conditions – user type: exactly matches ‘new user’
Technology – device category: exactly matches ‘mobile’

These are some of the segments that you can create and use to create your reports. To get more out of your segments you can view data with the addition of secondary dimensions to your reports. That will create a third level view of your data. For instance, you want to see organic traffic that came from users using mobile devices that landed on a particular landing page.

Segment: Organic

Audience => mobile => devices => overview

Primary dimension: device category
Secondary dimension: landing page

This report will only need advanced filtering on the primary and secondary dimensions to get to the desired device category (in this case mobile) and the landing page needed.

Conclusion

The use of secondary dimensions and segments helps in customising your reports to extract deeper insights into your data. They give different ways to visualise your data and realise pattens. I only highlighted a few customisations in this article. In Google Analytics, you can view more of this customisations and tools highlighted above.