Boosting eCommerce Conversions with Semantic Search

Recent advancements in Large Language Models (LLMs) are revolutionizing eCommerce search, traditionally reliant on keyword-based retrieval, by enhancing search relevance and sales conversions. The challenge of inconsistent and incomplete product data from multiple vendors in eCommerce marketplaces prompted Applaudo to explore Vectara’s LLM-based semantic search platform. Initially, a keyword-based approach yielded limited success, but integrating Vectara's semantic search with the existing keyword method improved search accuracy from 60% to 80%. This hybrid approach, leveraging Vectara's comprehensive infrastructure, reduced maintenance costs and highlighted the potential for combining established methods with innovative technologies to overcome data inconsistencies. Despite significant accuracy improvements, the evolving nature of eCommerce suggests that achieving perfect search results may remain an ongoing challenge.