Popular Searches

Popular Searches

Do I need anything more? Hmm, let’s see what other people are searching for right now before I check out...

Popular Searches give hints regards the most searched terms during a specific time. Shoppers can view the queries to be inspired when they’re not entirely sure what to look for. This type of suggestion can show up even before shoppers have started entering a query or when there are no search results to show.

Popular Searches

Spot the difference

Popular searches are the queries most used by others, designed to give hints on broad ideas or terms to start the search. Try not to confuse it with top-clicked product recommendations that direct people to specific products.

For example, before entering any query, shoppers will see a list of terms such as “long dress”, “mini skirt”, or “knit sweater”. If they select the first option, a search will launch displaying all long dresses available in your catalogue.

What’s more, Popular Searches refers to the top searches for the last day at your commerce. This doesn’t mean they’re trending terms, search terms that are becoming a trend since their popularity is increasing over the past days.

To give you a hint, you can identify popular searches mostly under labels such as “top searches” and “trending”.


Remember that other types of suggestions can display hints based on queries, search history, or even product references.

  • Anticipate shopper intent using machine learning technology.
  • Speed up query entry, especially on mobile devices.
  • Improve product findability. Guide shoppers to products in your catalogue they’re unaware of.
  • Enhance the shopper experience. Surprise shoppers with new ideas or alternative searches on what to look for.

Popular searches are generated by shoppers’ actions in the search UI. As shoppers perform different searches and actions in your commerce, behavioral information (queries, clicks, add to cart, etc.) is collected using the Tagging microservices and processed by the Search microservices.

The information is processed by the Empathize batch process to extract the most searched queries in terms of volume for a selected date range.

These candidate popular searches are then reviewed to check whether they are valid according to different filters (i.e. blacklisting, duplicity, etc.), resulting in a list of final Popular Searches that is ready to go.


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


Explore the interactive map to see how Popular Searches relates to the other Empathy Platform features and microservices.

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