When a shopper lingers on a page or clicks on an item link for more information, you can be fairly certain that they are interested in that product. When a potential customer types terms into your ecommerce search feature, you know that they are looking for something specific, but the terms your shoppers use may not match the description you use for products in your catalog. With Baynote, every customer’s search on your site is observed. We use these observations to create a taxonomy that links terms to items browsed and bought. Since people tend to search for items in a similar way, this allows Baynote to infer their intent.
When you know that a customer entered a set of specific search terms and ended up buying a specific product following their search, you can use that information to guide additional customers to the same product when they enter similar terms into your ecommerce search tool. There are few things as frustrating as trying to find something you really want to buy, but not being able to find it through onsite search. Baynote employs machine learning technology to constantly observe, capture and infer shopper behavior and intent and then deliver relevant results. Baynote technology adapts to an every changing range of products, predicts future buying patterns and enhances a customer’s experience.