Semantic search and explainability
The why and what behind semantic models
The Empathy Platform's use of semantic models is a key differentiator when providing explainable AI-powered search and discovery experiences for merchandisers. By enhancing the transparency and interpretability of data analytics, insights, and query & product performance, the explainability promoted by Empathy empowers merchandisers to make more informed and data-driven decisions to achieve their business goals.
Empathy's Semantics service is designed to capture the underlying meaning and relationships between search terms and catalogue products, shoppers' preferences, and market trends. By modeling these semantic associations, the AI-powered search and discovery experiences can generate recommendations that are more related to shoppers' intent and contextual meaning similarities without relying on external data sources or compromising data privacy.
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Learn more about semantic search in Empathy Platform and how it works on the Why semantic search page.
By providing visual insights into the inner workings of semantic search, merchandisers grasp shoppers' intent and better understand how Semantics improves their commerce store performance. Empathy Platform includes several features in the merchandisers' Playboard that uplift semantic search explainability for situations where shoppers' queries return low or zero results.
Semantics dataviz
The Semantics data visualization tool of the Empathy Platform Playboard displays how queries with no or low results have been enhanced with the Semantics service. This visualization helps merchandisers verify and understand the query performance after Semantics clearly. The increase of the interactions with your commerce store, such as clicks, add-to-carts, and checkouts, is compared with the interactions obtained from queries initially with no and low results, which gives a clear picture of the benefits leveraged by Semantics.
The Semantics data visualization is an essential tool for merchandisers aiming to reduce shoppers' frustration in situations of low or no results since data is analyzed to prove that the use of Semantics drives the success of the business strategies.
Product recommendations carousels in Explain
The Semantics service is a fallback mechanism for queries with zero or low results. In these cases, the Semantics service leverages its understanding of semantic relationships to generate relevant product suggestions that are closely related to the original query. These recommendations are usually displayed as product carousels that can inspire and guide your shoppers' experience.
To further enhance the transparency and explainability offered to merchandisers, these product recommendations displayed in carousels to your shoppers are also displayed in the Explain feature. This provides you with a realistic representation of how the Semantics service is performing in your commerce store. Once you click the suggested query's products carousel, you can check each product position, score, and scoring criteria.
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Constantly seeking innovation and high explainability, Empathy.co ideates a Play Vector visual explanation to shed light on what's behind semantic models. Read more in the Explainable AI in retail with Play Vectors blog post.