Can semantic search improve sales in e-commerce?

The aim of semantic search is to provide responses to user queries which contain the results expected by the user. This is made possible by a fundamental understanding of users’ intentions. For this purpose, a careful analysis is made of the context of the submitted query (to determine, among others, who the user is, where they are at present, when the question was asked, etc.) and of the relationships of the words used in the query (for example, their similarity in meaning to other words).

Why does this kind of solution work better than a standard search function on a product website? Users of e-commerce platforms may enter names that are close in meaning to the name of a particular product, providing opportunities for a kind of context search. However, this is a highly inadequate method of guessing the user’s intention. If the author of product descriptions fails to include appropriate synonyms, users of the system will certainly not be satisfied with the information they receive in response to their queries.

What does a semantic search engine do? It makes use of semantic relationships between words and informs the user about all products with a similarity to the item searched for. Moreover, in constructing a response to a consumer query, the search engine takes account of the user’s profile and situation. This approach makes the results less dependent on the author of the product descriptions, and adapts them to the user’s actual needs. This is particularly important when a wide range of products is on offer and when changes are frequently made.

The use of semantic search in e-commerce solutions leads directly to greater search effectiveness, and consequently to increased sales. This methodology allows a seller to offer customers the products that best answer their needs.

Can this approach be used in your business? We will be glad to learn what you think. Let’s talk about it – just get in touch with us!

Neural Machine Translation System Our Translator