3 min read

Top Products overview

Look! Those chocolate truffles have a good price! It’s Valentine’s Day, and everybody is already buying them!

Top-product recommendations show the top searched products. That’s to say, the most clicked products on the search results page, based on shopper interaction within a defined period.

Top product recommendations

Top-product recommendations are relevant product suggestions; they aren’t related to the query, but to products that matched previous searches done by other shoppers, instead. They're useful in multiple situations, especially when there are no search results to show. Whether a shopper lands on your shop and hasn’t written any query yet or if a search doesn’t bring back any product results, Top Products amaze shoppers with product discovery inspirations.

Spot the difference

Notice that top-product recommendations guide shoppers to specific products. When clicking a top-product recommendation, the related product description page displays without any further interaction. There's no need to search or navigate the results. Try to not confuse it with Popular Searches, which present the top searched queries to trigger a new search.

For example, “off-the-shoulder ditsy floral dress” can refer to a top-clicked specific product that redirects to the product description. But “dress”, “floral dress”, or “off-the-shoulder dress” express a currently top searched query, prompting a new search and displaying relevant results such as “off-the-shoulder ditsy floral dress”, among others.

You can identify top-product recommendations mostly under labels like Top searched items today or Other shoppers visited...


Remember that other types of product recommendations can inspire shoppers' product discovery, such as Semantics Recommendations, Brand Recommendations, or Next Products.

Try Recommendations to...

  • Improve product findability. Guide shoppers to products in your catalogue they don’t know.
  • Enhance the shopping experience. Surprise shoppers with new ideas or alternative products.
  • Handle shopper frustration. Suggest products when there’s no query to suggest or no results to show.
  • Speed up the search and discovery process, especially on mobile devices.

The inner workings of Recommendations

Top Products are based on shoppers’ actions in the search UI. As shoppers perform searches in the commerce store, the Tagging microservices track the clicked products, and the Statistics microservice analyzes the data to identify the most clicked products. For example, if over the past weeks shoppers have clicked on specific beach towels, swimsuits, and flip-flop articles, the same products are identified as possible recommendations.

After a number of days of data collection, the Top Clicked batch process generates the top-clicked product feed and calls the Index microservice to index the processed products in the search engine to make them available as recommendations.

At query time, Empathy Platform Interface X uses the Search microservice to retrieve the list of recommendations to display before, during, or after the search, depending on your implementation.


For correct performance, make sure that your current search service supports this type of feature.

Build your UI experience

If your Empathy Platform implementation includes the Interface X frontend layer, use the Recommendations module from the X Components library to build and customize your search UI experience. Learn more about the customization options on Design the Recommendations UI experience.