We just made personalization in CRO a lot smarter for your store

We’ve just rolled out some powerful updates across our Conversion Rate Optimization (CRO) suite, and they open up a whole new layer of personalization. These changes give ecommerce teams much more control over how they tailor the shopping experience, with more precision and flexibility than ever.

Here’s what’s new, and how to make the most of it.

1. Use custom product attributes to personalize recommendations & emails

Your product catalog holds more than just names and prices. It often includes rich data points like material, brand, flavor, or season. These are called custom attributes, and they help define what makes each product unique.

As shoppers browse your site, Hello Retail learns what they tend to prefer, for example, clicking more on certain colors, brands, or categories. These preferences are captured as a user bias.

Now, you can use both custom attributes and user bias to personalize Product Recommendations and Emails. The result: every shopper sees content that fits their current interests, while they’re still actively shopping.

A practical example:

Let’s say your store sells pet supplies. So, you have food that is different by pet type, like food for dogs, cats, birds, etc. You can now use that to recommend the right products.

This works especially well for your front page.

Here’s a quick setup:

Show recommendations with new products:

• Create a recommendation box using the “Recently Created” algorithm.
• Set how many days count as “new” (e.g. 60 days).
• Add a filter that matches the user’s bias toward a specific animal type.
• Add a fallback rule to make sure there’s always something relevant to show.

In short:

You can now personalize product recommendations and email content using your own catalog fields, like style, material, or occasion, matched with each shopper’s preferences. It’s now much easier to show the right products to the right people.

2. Smarter personalization with list-based attributes

Many products in your catalog don’t just have one attribute, they have several. A t-shirt might come in three sizes, or a chair in five colors.

These are what we call list-based attributes, and they’re stored as Extra Data Lists in Hello Retail.

Now, personalization for search and recommendations supports these attributes too.

This means you can now tailor results based on combinations of values, not just single tags.

For example:

• Colors (red, green, blue)
• Sizes (S, M, L)
• Features (e.g. waterproof, recycled, breathable)

A practical example:

Imagine you’re selling fashion items, and your dresses include the attribute Style, with values like minimalist, romantic, sustainable, or boho.

One shopper tends to engage with items labeled “sustainable” and “minimalist.” Another clicks more often on pieces tagged “boho” and “romantic.”

With list-based personalization, your search results adapt accordingly. If both users search for summer dress, they’ll each see options that reflect their style bias — even if those keywords aren’t part of the search.

See below the example of Search configuration settings.

In short:

If a product has more than one value (like multiple colors, or styles), Hello Retail can now personalize based on those combinations. So shoppers see results that better match what they’ve been browsing, even if they didn’t search for it directly.

Bonus tip: How to use the Hello Retail AI attributes

Not all personalization relies on product tags or category data. Hello Retail’s AI-powered attributes, Budget Zones and Product Clusters, give you additional ways to tailor the shopper experience, even when your catalog data isn’t perfect.

In short:

Budget Zones automatically group products based on their price levels, so you can easily personalize product recommendations and search to align with a shopper’s spending expectations.

In short:

If your categories are vague, inconsistent, or just missing, Hello Retail automatically analyzes your products and assigns them to Product Clusters you can use for optimization and personalization.