Boosting eCommerce Conversions with Semantic Search

Boosting eCommerce Conversions with Semantic Search` is a blog post that explores the limitations of traditional keyword-based approaches to eCommerce search and highlights the potential benefits of combining these methods with modern semantic search techniques using Large Language Models (LLMs). The authors, Applaudo, describe their experience in implementing Vectara's LLM-based semantic search platform on an existing eCommerce marketplace. They initially developed a conventional keyword-based search engine but faced challenges due to inconsistent product descriptions and varying conventions among retailers. To overcome these issues, they combined traditional keyword-based approaches with modern semantic search techniques using vector embeddings, achieving improved accuracy rates of 80% and lower Total Cost of Ownership. The authors conclude that combining conventional methods with newer technologies can lead to significant improvements in search relevance and effectiveness.

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