Seven Segments Every Ecommerce Site Should Use for Personalization and Analysis

First and foremost, you want to be able to distinguish your visitors who have never been to the site from everyone who has been there before. As this group might be unfamiliar with your brand or how your site works, they may need specific messages or experiences aimed at educating them on the differentiators of your brand or your shipping and returns policies, assuring them they have landed in the correct place and why. In this example below, Rue La La explains to first-time visitors how its members-only boutique works.

When you can identify someone who has purchased before, you are able to recognize your true customers. You want to avoid providing introductory messages to this group, because you don’t need to reintroduce yourself to them. You can instead suggest items that pair with products they have purchased in the past.

You can also look into how the behaviors of this group compare to that of a group of shoppers who have never purchased. What sources brought them to the site? Did they engage with any content that non-purchasers didn’t? This analysis can help you identify some campaigns to test to try to convert non-customers in the future.

Knowing who your loyal or high-value shoppers are is critical. With that information, you can send a targeted email with special discounts or early access just to them. You can ensure that the website incorporates plenty of personalized elements so loyal customers know that you recognize and appreciate them. You can also analyze the differences in behavior between these customers and those shoppers who have never purchased before to see if there is anything that can be learned about how to create more high-value customers.

Loyalty is defined as a combination of engagement and spend — meaning that in addition to spending relatively more than the average visitor, loyal customers also visit the site more regularly and spend a lot of time shopping. But every company has a different customer base, so it’s important to figure out what loyalty means for your business before you begin creating this segment.

Sending cart abandonment emails is a common tactic for retailers. But if your personalization solution can add shoppers to segments in real time, you can show a message to shoppers who are attempting to leave the site, incorporating items from their cart and offering an incentive (such as in the image below).

Every retailer is familiar with product recommendations, which should be individualized so that each person sees products in their preferred categories, brands, colors, or any other relevant attribute. Those types of experiences are driven by machine-learning algorithms, so segmentation isn’t needed there. But there may be other times when you want to show promotions of a certain category only to visitors who care about that category. In those cases, you will want to have one segment or more that contains shoppers whose favorite category is X (depending on the categories you sell, of course).

“Favorite category” should be defined as the category in which the shopper has spent the most time within a specified timeframe, which should be determined by you and your team. You could, of course, determine someone’s favorite category based on clicks alone, but you may be missing out on a shopper’s true intent. A shopper can click on a product or category as many times as they like, but are they showing more engagement by spending the most time there? That’s the real question.

Once you’ve created this segment, or segments, more likely, you can tailor your homepage images and headlines to promote each visitor’s favorite category (such as nursing shoes, in the image below), or you can send emails that contain promotions for the category that is most relevant to each recipient.

These are just the seven segments that are relevant to most retailers. There are many more segments that you can create that are more tailored to your needs. And you can combine various segments above to create even narrower segments — such as high-value shoppers from New York whose favorite category is footwear — to use for targeted personalization and analysis.

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