Assisted Search

Assisted search refers to search experiences that use AI to help users find what they are looking for more effectively — going beyond keyword matching to interpret intent, handle natural language queries, correct errors, surface semantically related results, and provide guided navigation such as suggested refinements or clarifying questions. It encompasses techniques including vector search, query understanding models, spell correction, synonym expansion, and conversational search interfaces.

In e-commerce, search is one of the highest-value surfaces on any digital storefront: shoppers who use search typically convert at significantly higher rates than those who browse. Assisted search directly impacts revenue by reducing zero-result pages, surfacing relevant products for ambiguous or long-tail queries, and guiding uncertain shoppers toward purchase-ready results. As large language models become embedded in search layers, assisted search is evolving toward fully conversational product discovery — where customers describe what they need in natural language and the system interprets context, constraints, and preferences dynamically.