Segments are one of the most powerful features in Google Analytics – you can use segments to examine a subset of your data.
Segments are flexible and quick to set up, so they are great for exploratory work.
But once people learn how to create and apply segments, they often hit a stumbling block. They know how to use segments, but they don’t know how to draw meaning from the data.
In this post, I’ll look at a few different scenarios for finding meaning. This is not a comprehensive list. Instead it’s a first step in thinking about how to use segments to interpret audiences.
And if you want background on segments before diving into this post, check out Introduction to Google Analytics Segments.
Conversions
Goal
Understand how users who convert behave. Derive information about what is important for a conversion.
How to Segment
Google Analytics has a built in Converters segment that relies on goal completions and transactions. You might be able to use this segment as is or you might want to copy it and adjust it.
Approach
Once you have a segment in place, one research path would be to look for typical behavior. The exact questions you should ask depend on your site. But to illustrate:
- Landing Pages:
- What are the most common landing pages for users who convert? Why are these landing pages the most common?
- One reason to look at this is that it can give you insight into how far people are into the sales funnel when they make a purchase. For instance, if they tend to land on product pages, perhaps they previously researched and bookmarked the product page or they’re following a link from another site.
- Pages
- What pages are users looking at prior to converting? Are there any that they are not seeing which are part of a common path?
- You may find problems on pages users typically view but are negatively correlated with conversion.
- Events
- Are any Google Analytics events associated with conversions?
- For instance, are users more likely to submit a lead form if they trigger an event by viewing a video? Are there other events that correlate positively with a conversion? Do these events tell you anything about the questions users want to answer before they convert?
Comparisons
Goal
Comparing sessions that did and did not include a key site behavior can lead to unexpected insights about audience motivations and behavior.
A key site behavior is any action that is important for the goals of the site – it could be a purchase, triggering an event, visiting a specific page, etc.
How to Segment
To make the comparison, create two segments. One segment should include the key site behavior. The other segment should exclude the key site behavior.
Approach
Once you have the segments set up, apply them to the reports and look for differences and similarities.
In Google Analytics, you can use events to measure user interactions with a site, eg you can set up an event to track button clicks.
I analyzed a site where I compared sessions that included an event versus those that did not. The event was triggered by a user saving content.
The sessions that included the event had fewer pages per session, whereas the sessions without an event had more pages per session.
Comparing the two groups led me to consider why they would behave differently. How did the two groups differ in their motivations and goals?
This data combined with other data suggested that the users who triggered the event were visiting the site with a pre-defined goal in mind, whereas the users who didn’t trigger the event were exploring content.
A possible avenue to follow based on this insight was how to support both audience groups. In the case of the users that triggered the event, how to make an event as easy as possible. In the case of the exploratory group, how to help them find what they needed in order to convert.
Without segments, I wouldn’t have been able to compare these two groups and develop a hypothesis about why they were behaving differently.
Site Sections
Goal
Understand how the different parts of the site are tied together from the audience’s point of view. This can help you understand audience motivations, goals and where they are in the funnel. It can also help reveal issues with your site structure.
How to Segment
The first step is to decide what section you want to use to define your segment.
Perhaps your site has a solutions section divided up by industry and product type. The path for all industry solutions starts with /solutions/industry. You can create a segment that includes a page view of /solutions/industry.
Approach
You’ve set up a segment for sessions that include a page view of a page with the path /solutions/industry.
That could include the top level page for the solutions by industry section as well as industry-specific pages, eg /solutions/industry/banking.
Questions would vary greatly by site, but a few possibilities:
- What were the landing pages?
- For instance, suppose a lot of the landing pages were in the resources section. This would suggest that users may be starting with your content and then getting interested in your product offering. Depending on the details, that could be great or it could point to a problem.
- What content other than /solutions/industry was viewed?
- Was other content viewed or did the majority of the sessions include just the industry solutions pages? For instance, depending on the site, if the majority of the sessions included just the industry solutions pages then it might be worth adding in links to other relevant content.
- Does viewing this section correlate with conversions?
- How does the conversion rate for this segment compare to the site as a whole? Is it much lower, higher or about the same? Why could that be?
Remove Logins
Goal
If users come to your marketing site to log in, it can severely skew your data.
Logins inflate your session numbers, which impacts conversion rates, bounce rates, pages per view, etc.
By removing logins, you can develop a clearer picture of user behavior.
How to Segment
You can remove sessions that include a login through segments.
The recommended way to remove logins with a segment is by using a custom dimension. The steps at a high level:
- Set up a custom dimension for logins
- Create an exclude segment based on your custom dimension
- Apply the segment to the Google Analytics reports
However, setting up custom dimensions can be challenging.
If it is not possible to set up a custom dimension, you can create segments based on user behavior, though this is not best practice.
- Page Views:
- If there is a unique page that is tracked by Google Analytics
- AND only your logged in users view it
- AND all logged in users view it
- you can create a segment that excludes sessions that include that page
- If there is a unique page that is tracked by Google Analytics
- Depending on your site and Google Analytics set up there may be other workarounds.
Approach
Removing logins may reveal trends and patterns that were hidden.
Once you have applied the segment, one approach would be to review your KPIs. Has anything improved? Has anything worsened?
Also look for actions you need to take on your site. For instance, if users logged in on the homepage it could have artificially depressed your homepage bounce rate. Once you remove the login sessions, you may realize you have to re-think your homepage.
A Last Word
Segments are powerful, but they can be subtle and difficult to use. As I mentioned in a previous post introducing segments, know what question you want to ask before you set up the segment.
You may not know if your question will turn up anything interesting. But by rapidly iterating and following where data leads, you can use segments to find interesting insights about your audience.