In its second-largest acquisition, Amazon buys the company for $970 million.
Natural language processing of terms that customers enter into search boxes allows retailers to analyze what customers are looking for and present products and content in ways that are more likely than old-style results strings to increase sales.
Site search has become an active merchandising tool for online marketers-a long way from the list-of-links paradigm of a few years ago. “No one used to think of site search as an opportunity to capitalize on the user experience. It placed the burden on the end user to figure out how to make the query request and how to navigate the answers,” says Tony Frazier, senior vice president of marketing at search and navigation technology provider iPhrase Technologies Inc.
At iPhrase today, that`s not the case, due in part to natural language processing capacities at the core of the site search technology it provides to marketers directly and in cooperation with CRM technology vendors. Natural language processing parses multiple elements of a search query to provide a deeper understanding of query intent, Frazier says. “Natural language processing is used as a means to make it easier for the user to express himself so we can understand the intent of what he needs. We also use that information to be very directed about how we present the content we retrieve and how we leverage that content interaction to create opportunities to influence,” says Frazier.
At iPhrase client Sephora.com, for example, a query on “dry hair” may not only deliver relevant hair products Sephora wishes to promote, but also related content, such as a magazine article that offers guidance on the subject. “They are using the same business rule facility to directly promote product, and also to promote non-product content that educates a user in how to solve the problem-and along the way, sell more product to facilitate that,” Frazier says.