The first step on the path to implementing these strategies is to understand the difference between the two. 

The Difference: a high-level view:

Segmentation is done manually. You divide your visitors/clients/customers into groups or categories, based on general attributes like age, gender, country, profession, etc. You then manually create rules to show those groups content you think will be most relevant to each.

Personalization is automated, using an artificial intelligence (AI) algorithm that generates unique and relevant content for each individual, mostly based on their past interactions on your website.  


What it looks like: Say you sell internationally and would like to increase raincoat sales in Spain. With a segmentation strategy, you set up your site so that visitors with an IP address from Spain would:

  • See predetermined content: maybe a landing page that features raincoats on rainy days (IF country = Spain and IF weather = rain).
  • Newsletter subscribers in Spain receive a specific email featuring the raincoat campaign
  • Men in Spain receive a different promotional email than women; each with gender (segment) specific products and links. 

    In this example from Dynamic Yield, you can see the different types of information used to segment: User Type, Device Type, Country, Weather Conditions, Lifetime Value, Objective.

The upside: Segmentation can create helpful and more relevant interactions. It also allows you to find out which segments spend more. You can then focus your eCommerce optimization budget on content and UX experiences for those more profitable segments.

The downside: Segmentation relies on generalizations that can be frustrating for a user when they experience an irrelevant customer journey. You know the feeling, right? It’s like being retargeted with a product you’ve already purchased. Also, someone from Spain might not want to be limited to Spain-specific (or segment-specific) content. It is also time-consuming to manually identify all the possible segments and then create, test, evaluate and optimize relevant content.  


Personalization software uses every action taken on your platform to automatically adjust and optimize the content and customer experience for the visitor, using algorithms to figure out what is most likely to lead to conversion and/or increase average order value (AOV) – or whatever objective you may have chosen (newsletter subscription, for example).

By leveraging multiple data points, you can generate unique content for each consumer, showing each visitor the content and products that they are statistically more likely to purchase, quickly improving your conversion rates and average order value.

What it looks like: Stokes, a housewares retailer, implemented Dynamic Yield’s personalization engine. The recommendation widget, seen here on the catalog page, automatically suggests interesting products to each user, based on the user’s previous interactions with the site (clicks, page views, likes, products added to cart and products purchased). A few months in, this widget already generates up to 10% of the retailer’s total eCommerce revenue each month, quickly surpassing the initial ROI threshold. 

Where should you invest first? 

Personalization or segmentation?

If you aren’t doing either, start with segmentation. Email segmentation, more specifically. Though, if you’re serious about increasing ROI, and if you have a budget and resources, you may as well invest in personalization right away.

Find a technology partner who specializes in personalization and who understands your eCommerce objectives and ecosystem (Hi, we’re Absolunet!) to properly implement personalization, including measurement.

To get started with segmentation and personalization, increase average order value and raise value per session, get in touch with our eCommerce Consulting + Advisory Service team.  


Written in collaboration with Chiara Fumagalli, Absolunet’s Digital Personalization Expert

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