Most of the content centered on customer segmentation for ecommerce tells you how to segment based on the data available in Google Analytics. That can be helpful — it enables you to break out customer segments by facets such as traffic source and browser and understand how certain ecommerce metrics vary across those different segments.
But if those are the only customer segments you use and the only metrics you segment by, you’re missing out on key behavioral information such as:
- How click behavior varies across customer segments
- Whether customers who abandon their carts behave differently across your website
- How website behavior varies between long-term customers and newbies
That’s information that can help you better hone your personalization efforts and your marketing strategy overall.
Note: Looking for more detailed and reliable customer segmentation? Sign up and try Crazy Egg free for 30 days to gain access to visitor-based and behavioral data about the people visiting your website.
4 Ecommerce Segments You Can Track in Google Analytics
In this article, we cover the four main segments you can break out in Google Analytics. Then we take it a step further and explain how Crazy Egg’s visitor-based data opens up a whole new world of behavioral segments and adds another level to Google Analytics segmentation.
(If you’re already familiar with segmenting via Google Analytics, you can skip ahead to the section on how Crazy Egg adds more targeted ecommerce segmentation options.)
There are four main segments ecommerce businesses can create based on the data available in Google Analytics. You can segment users by:
- Referring source
- User type or frequency
- Geographic location
- Browser and device types.
By segmenting your customer base by these dimensions, you can quickly get a sense of how engagement and conversion vary (if they do) based on each segment. They can tell you if returning users spend significantly longer on your ecommerce website than new users, for example, or if customers from a particular country or city convert more often than customers in other locations.
Referring Source Segments
To access the referring sources report in Google Analytics: Acquisition → All Traffic → Source/Medium.
By breaking customers into segments based on where they came from before landing on your ecommerce site, you can get a sense of the quality of traffic you get from different referring sources.
You can see, for example, if a higher percentage of customers coming from Google Ads convert on their first visit versus those coming from social media (say, Instagram).
With that information on hand, you may consider testing different conversion paths for the two channels. You can send Google Ads visitors directly to product pages (where they can buy right away). For Instagram visitors, you might test pairing a product page with a content asset, discount offer, or other mechanism for capturing their email—that way, you can remarket to them and keep those users moving through the funnel.
User Type Segments
To access the user type report in Google Analytics: Audience → Behavior → New vs. Returning.
When you break customers into user type segments, you get a sense of engagement and conversion metrics for users who’ve been to your website before compared to brand new users.
Based on the breakdown of new vs. returning user segments, you can see which pages new and returning users typically visit, for example.
You can figure out which pages each segment converts on and learn if new users tend to buy certain products more so than returning users (and vice versa). With that information, you can test adding personalization to your homepage that recommends different products to new and returning visitors.
Geographic Location Segments
To access the location report in Google Analytics: Audience → Geo → Location
Segmenting your customers based on geographic location is a common option—and it enables you to get a sense of engagement and conversion across countries, cities, and continents. This information can be invaluable in allocating marketing and advertising budgets and targeting your paid campaigns.
You may see, for example, that customers accessing your ecommerce store from Canada have a higher conversion value than those accessing from the U.K. With that information, you could allocate more ad spend targeting Canadian customers to increase conversion value more effectively.
Browser & Operating System (OS) Segments
To access the browser and OS report in Google Analytics: Audience → Technology → Browser & OS
When you segment ecommerce customers based on the browser, OS, and device type they use to access your website, you can get really valuable insight into your website’s usability across devices — plus how that affects engagement and behavior.
For example, if you find that conversions are particularly low for one browser — say, Safari — you can take a deeper look at why. You may find that the checkout button on your shopping cart page doesn’t render correctly when viewed on Safari, and a few simple adjustments based on that information could drastically increase conversions on that platform.
Crazy Egg Adds More Targeted Segmentation Options for Ecommerce
There’s a lot of information to be gleaned from Google Analytics — but the free tool has one limitation that makes a huge difference for ecommerce marketers: All of their data are based on sessions.
In other words, Google Analytics doesn’t tie multiple sessions from the same user together. So you can create customer segments using Google Analytics, but they aren’t as reliable as if they were segmented by actual visitors.
At Crazy Egg, we use visitor-based data — and that allows you to create more targeted customer segments based on our visitor behavior data, plus your own ecommerce customer data. It also enables you to add another layer of analysis over top of your Google Analytics segments.
When you run heatmaps and other reports on your online store, Crazy Egg allows you to filter results for our Confetti, Overlay, and List Reports to see click behavior across 22 different dimensions.
By filtering for Referrer, New vs. Returning, Country, Browser, Operating System, and Device Type, you can get more behavior data on the segments identified in Google Analytics.
That’s important because, when you use Google Analytics data alone, you’re left with a big blind spot around what happens between the time a user gets to your website and when they ultimately convert. Did they scroll all the way to the bottom of the page? Did they click to read more product reviews? Did they view additional images of the product?
Answering those questions gives you a more holistic view of each customer segment and what gets them to buy.
Here’s an example of that information in action. In the Confetti Report below, we filtered clicks by new users. We were originally interested in how their behavior on the sales form varied from returning users. But the highlighted yellow box shows us that a sizable chunk of those new users are clicking on the brand’s logo—an escape hatch leading them out of the sales funnel.
That’s a hint, but it doesn’t tell us why so many new users are abandoning the conversion process. By looking at the Overlay Report on the same page, we can see that most of the new visitors clicking the logo came from Google search.
That tells us those users probably aren’t ready to buy—they need more information first. With that info, we can redirect those users to a page designed for the top of the funnel instead.
Additional Ecommerce Customer Segments You Can Create Using Crazy Egg
In addition to giving you more contextual information about existing customer segments, you can also break out even more specific and targeted segments using Crazy Egg.
Our heatmap tool allows you to define up to five user variables. That means just about anything you can measure and pass along to Crazy Egg can be tracked in your Snapshots (that’s what we call our five different user behavior reports).
By defining those custom user variables, you can view click behavior across your website based on these five additional ecommerce segments:
- Customer loyalty (loyal customer, first purchase) and lifetime value (LTV)
- Type of buyer (bargain hunter, habitual buyer, subscription, big spenders, etc.)
- Cart abandoners
- Average order value
- Other customer data including psychographic and demographic information (such as gender, income, style, and age).
By filtering Snapshots by style, for example, you can get valuable insights on how different customers navigate your product catalog. That makes it possible to create dynamic and personalized catalog pages and related products suggestions.
Here’s a sample of our Confetti report filtered by a given user variable:
If the user variable is broken down by the customer’s style, you can see that the customers represented in green are more interested in products lower on the page. In this case, you might test a dynamic shopping experience that places those products higher on the page for this particular customer segment.
Note: Looking for more detailed and reliable customer segmentation? Sign up and try Crazy Egg free for 30 days to gain access to visitor-based and behavioral data about the people visiting your website.
How to Track Visitor-Based Ecommerce Segments with Crazy Egg
If you’re not a programmer, you’ll want to bring in your web developer for this. Because Crazy Egg doesn’t automatically know the value you want to track, you’ll need to tell our software via code.
First, you’ll start by deciding what you want to track. For our purposes here, let’s say you want to track users who are logged into their account versus those who aren’t. Once you’ve made this decision, you need to figure out how you’ll identify these visitors (your developer or programmer can help with this).
Many of our users make use of the Cookie Files they set in order to track additional information. So, for example, if you have a “logged in” value in a cookie, you can set that as a user variable in Crazy Egg.
To do that, you’ll need to write code to read the cookie and then set it as the value. How you do this is up to you. Here’s an example of how you would pass that data onto Crazy Egg, using the CE_READY() function:
function CE_READY(){
var isLoggedIn = ?; // Customer must provide logic for setting isLoggedIn
if ( isLoggedIn )
CE2.set(1,’logged in’);
else
CE2.set(1,’not logged in’);
}
Once your programmer sets up your customer user variables, you’ll begin to see this data in both the Confetti and Overlay Reports you run.
Note: Crazy Egg automatically tracks UTM campaigns and parameters you’ve defined on your website — so there’s no need to use custom user variables for these.
Better Ecommerce Customer Segmentation
In the ecommerce world, customer segmentation isn’t optional anymore — it’s table stakes to enable marketing efforts that keep pace with your competition.
When you add click behavior data to existing segments and use Crazy Egg’s custom user variables to break out additional behavioral segments, you make it possible to:
- Run retargeting and other personalized ads
- Offer customers dynamic product recommendations
- Personalize product detail and landing pages
Those are high-value aspects of ecommerce marketing campaigns — meaning, when they’re done correctly, you can see big returns on those efforts.
Note: Looking for more detailed and reliable customer segmentation? Sign up and try Crazy Egg free for 30 days to gain access to visitor-based and behavioral data about the people visiting your website.
