Fast Simon Launches Vector Search for Ecommerce
Fast Simon's advanced AI model learns from queries and shopper behaviour, so results improve over time.
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Fast Simon, a provider of shopping optimisation solutions, today released Vector Search with advanced artificial intelligence for ecommerce to help ecommerce sites match buyer intent, personalise the shopping experience, answer questions, and make product recommendations.
Rather than matching keywords, Vector Search uses natural language processing and neural networks to analyse queries. Vector embedding maps the words from the search to corresponding vectors to detect synonyms, intent, and ranking, and it clusters concepts to deliver more complete results. Fast Simon’s advanced AI model learns from queries and shopper behaviour, so results improve over time.
“While many e-commerce search queries today are just one to two words, Gen Z tends to search differently. They often use full sentences and look for contextual results that match their intent. This shift requires a new approach to search that goes beyond keywords to understand the meaning,” said Zohar Gilad, CEO of Fast Simon, in a statement. “As the next generation of shoppers, meeting the expectations of Gen Z is crucial for retailers who want to stay relevant.”
