When someone enters a search on your site, you want the most relevant results to be returned for that shopper. Athos Commerce processes user search queries and returns results which are scored based on how they match the search query and then listed in descending order of relevance. The relevancy ranking is determined by a number of factors.
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Watch this video to learn more about relevancy scoring.
It all starts with your product data.
Your product data feeds are what power Athos’s search and filtering, and an optimized data feed will produce the most relevant results for your shoppers. For a list of fields to include in your data feed, see the Athos Data Sources Guide. Athos will look through all of your product data to make sure we’re leveraging the right fields in the proper way to deliver the best search experience.
The initial search results and number of products returned are based on keyword match. Only products that contain a matching keyword will be shown.
After the initial set of results is returned, product awareness is applied to the search query and to the products to learn the naming conventions and determine the shopping intent. Product Awareness uses natural language processing principles to look at the subtle differences in the search query to classify or group different products. A good example is searching for “vanity mirror” versus “vanity with a mirror”. With product awareness, when someone searches for "vanity mirror", Athos is able to determine that the shopper is looking for a mirror. In contrast, when they search for “vanity with a mirror” they are looking for a vanity.
Next is product phrasing. We take into consideration what fields the keywords are found in, how much other data is in these fields, and in what order the keywords are found within the fields. For example, if someone searches for “Blue shirt” and “blue shirt” appears in the name field, it will be ranked higher than a product with “shirt” in the name field but with “blue” appearing in the color field.
In addition to textual relevance, business logic and merchandising is also applied to the result ranking. Learn more about how products are arranged.
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