In a new blend of search and web 2.0 technology, content guidance software vendor Baynote Inc. is offering a new hosted service that delivers product recommendations to site visitors based in part on what search engine delivers them to the site, and the collective on-site behavior of those visitors.
Baynote’s Community-Guided eCommerce technology as deployed by retailer sites captures the behavior of shoppers on the site and ties it to their referral source. It uses that information to build audience segments, then recommends products to a shopper based on what other like-minded shoppers in the identified segment have browsed and bought; for instance, displaying those recommendations on the home page or a product landing page.
By uncovering niche audience segments, the technology allows retailers to profitably offer and sell a wider variety of products than would be profitable for a brick-and-mortar retailer to keep in stock, according to Baynote.
Besides the peer-driven recommendations, the on-demand community-guided e-commerce solution also adjusts for seasonality and fads, recognizing shifts in visitor behavior over time and automatically adjusting the recommendations delivered to optimize conversion. Additionally, it identifies product gaps in failed searches on a site, automatically optimizes landing pages by recognizing site visors by referral source and then displaying visitor-specific recommendations. It also uses shoppers’ collective search, shopping and buying behavior on a site to automatically tag products on a participating site, and automatically does A/B testing on a site to measure results driven by Baynote technology against those that aren’t.
“Baynote has a clear understanding of what products shoppers actually consider versus where they click, and matches that wisdom against a visitor’s true intent,” says Jack Jia, founder and CEO. Early users of the technology solution have reported revenue increases of more than 20%, according to Baynote.