Reduce no-results search queries and improve relevancy at a top-five retailer whose product catalog consists of a broad selection of products but limited varieties of each product type.
Deploy semantic vector search with a proprietary, deep-learning encoder called Never Null that learns from customer behavior to associate queries with products that have a corresponding purpose.
Over the Cyber Five, zero-results queries were reduced by 91%, and improved relevancy resulted in search-influenced orders increasing by 30% and search-influenced order value by 28%.