Blocks for everyone. 6 useful segments for you
This article complements previous posts on creating a persona and engaging with audiences in Google Analytics. If you didn't have an opportunity to read them so far, have a look here: Why my audience is the Persona? and How to create your hero (which Analytics will help with).
Example configuration were prepared using Universal Analytics.
As you already know, segments are useful to understand your audience and to test whether your imagination about what they are doing on your site makes sense. By reading this article, you will learn about segments, what maybe also inspire you to further "creativity". If you are already looking for specific solutions, go directly to the part you are interested in.
Segment of users from social media
Blog readers segment for checking conversions
Abandoned cart segment from e-commerce reports
Availability of segments in your account
What are the segments?
Let's start from the beginning. According to Google documentation:
„A segment is a subset of your Analytics data. For example, of your entire set of users, one segment might be users from a particular country or city. Another segment might be users who purchase a particular line of products or who visit a specific part of your site.”
In practice, this means that you define the characteristics of the target group of recipients you are interested in, and from all data collected in one Analytics view, those meeting the given conditions are selected. Or you can imagine it as a kind of strainer with holes of a certain shape. Only those that pass through the strainer selected by you will fall into the prepared bucket-
segment.
Note: In this article, I only cover user segments. If you are interested in conversion segments, please see the Google documentation (link below the article).
Segment limits
As with everything, you can also create a limited number of segments. Fortunately, the limits are high so you don't have to worry about them too much. However, they depend on how you share the segments, so I'll put this information here.
If segments are set to be available to one user in each Universal Analytics data view, then there can be 1000. (Segment Availability: I can apply / edit a segment in each data view.)
If segments are only available to one user in only one data view, there can be a maximum of 100. (Segment availability: I can apply / edit a segment in this data view.)
If segments are available to all users in only one data view, there can be a maximum of 100. (Segment availability: Colleagues and I can apply / edit a segment in that data view.)
The maximum date range for user-based segments (which is all discussed here) is 93 days. If you choose a longer period, it will be automatically reduced to 93 days.
Also, note that you won't apply segments to your Google Ads cost reports or Multi Channel Funnel reports. For the latter, you will need conversion segments (link below the article).
What do we use segments for
Now that you know what segments are and how many you can create, it is still worth knowing what they will be used for. Segments as subsets are used to compare data to other parts of the dataset or to the whole. In practice, it looks like you enter the report, for example, Behavior > Site Content > All Pages, and for example, Logged In Users in the All Users segment, which is shown by default. The report updates and shows you data for both audiences, and you can see how active the logged in users were and whether they made multiple conversions and what kind. You can see which pages were viewed by them most often, how long sessions lasted and whether the bounce rate is at a satisfactory level.
You can use up to four segments in one report at once, and when you move on to the next report, the segments will stay in use. They will not disappear until you disable them or exit Analytics.
Segments useful for you
Now let's move on to the examples. Below you will find the configuration and how-to-use descriptions of the five segments that will be useful to you.
1. Persona segment
If you already have your persona (or a few) then create an "Analytics image" of it. I will use a persona named Daan, which was created in the article How to create your hero (which Analytics will help with) for Monika, a Norwegian language teacher. Let's start with how to "translate" the data from the persona into the segment settigns.
Age: 30 => Demographics > Age 24-34
Gender: male => Demographics > Male gender
Location: Rotterdam (The Netherlands) => Demographics > Location Netherlands (or the city of Rotterdam)
Language: English => Demographics > Language includes en
Profession: architect
Income: EUR 75,000 / year
Interests: contemporary architecture, mountain tourism
Values: openness to cultural diversity, freedom of travel
How to create such a segment?
Go to Admin > (right column) View > Segments > + ADD NEW SEGMENT
From the left menu choose Demographics and select all conditions in the middle, i.e. age, gender, language, and location.
In the right column you will see a summary of all selected conditions. It is especially useful when you select them from different categories, such as Demographics and Behaviour, and you may not be able to see all selected items at the same time.
Name the segment and save it.
Daan's "Analytics Image" is ready to use!
You can check whether "Daan" appears in reports, whether it uses mobile devices more often or prefers desktop, what pages it displays and how often it returns.
Are there many people in your reports matching your persona?
2. Segment of users from social media
Of course, you don't have to limit yourself to social media. In this way, you can also set up a segment of users coming in from other sources, for example branded media or paid advertising ("cpc" medium).
Go to Admin > (right column) View > Segments > + NEW SEGMENT
From the left-hand menu, select Advanced > Conditions, and in the middle, select Filter - Sessions - Include. Then select Source - Contains - facebook and click on the "OR" button on the right. In the next row, enter the name of the next social media. Keep adding rows as long as you keep adding one source at a time.
Note: Enter the sources names in lowercase because the source is taken from the URL, so it will be facebook, linkedin and tiktok, not Facebook, LinkedIn and TikTok. Additionally, Analytics will suggest source names based on the data already collected, but you don't need to enter m.facebook.com, l.facebook.com, and lm.facebook.com separately. Since the condition is set to "source contains", only one specific fragment of the address is enough for Analytics to catch them all. Therefore, "facebook".
Yes, you can also create a separate segment for each of these sources and compare them with each other.
Name the segment and save it.
Ready!