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How does vector search work?

Search for an “outfit for a summer day,” and see your e-commerce search returning hyper-relevant product suggestions: flip-flops, short summer dresses, sunglasses, and bikinis.

Vector search works by converting text and images into vectors (numerical representations), which are then used to measure similarity with other products and suggest the most query-matching ones.

Vector search is far more accurate and efficient than traditional keyword-based search, which relies on exact matches and predefined rules.

The technology behind Vector Search

Word2Vec - meaning beyond words

Vector search uses the Word2Vec technique to convert text and images into vectors and to find similar products based on those vectors.

That’s how LupaSearch can understand the user’s query and match it to relevant products according to their semantic similarity.

Search experience users cannot resist

Vector search, based on NLP and combined with other advanced search technologies (Semantic Search and Machine Learning), supercharges customer experience and delivers relevant-only search results.

The search results are not only accurate but also fast, even on large and varied data.

Customer is choosing products

Search for products from photos

Took a screenshot of a nice jacket on social media? Did you see the sofa you always wanted at your friend’s place?

Upload a product photo to LupaSearch, and the vector search engine will find similar products without you needing to describe them.

Yes, LupaSearch automatically extracts specific product attributes like color, material, and use case.

Search for products with no descriptions

Not much of a writer? Your products don’t have to have extensive product descriptions for the search engine to understand their function and most critical attributes.

Vector search can extract information from product images, even if there is no text, and deliver query-matching product suggestions.

AI driven search displays results
LupaSearch autosuggests search terms

Search for products in separate categories

Vector search can replace (or complement) the need for faceted search. Vector search can apply product filters automatically by selecting products that match your query in multiple aspects.

For example, if a user searches for "hiking clothes for summer," the search engine will select products according to season, material, and function with no additional filters needed. (Of course, LupaSearch always leaves an option for users to use them.)

Want to learn more?

Learn about all features and benefits from LupaSearch.

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