Improving product searchability is essential for any commerce website. Traditional search experiences typically rely on keywords and synonyms, but they often fail to capture the user’s intent effectively. Understanding intent through keywords alone is challenging, as many words in English have multiple meanings, and their true meaning depends on the context of the entire query. To address this challenge, we can leverage vector embeddings from AI models alongside a search platform that supports vector-based retrieval, enabling intent-based search and delivering more relevant results beyond basic keyword matching.
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