Fresh Relevance helps online retailers reduce bounce rate with new AI-powered Price Affinity Predictor
BOSTON, US AND LONDON, UK MAY 28th, 2020 – Fresh Relevance, the real-time personalization and optimization platform, today announced that it is helping online retailers engage new website visitors and improve click-throughs with its new Price Affinity Predictor. Developed in collaboration with the University of Portsmouth, it uses powerful artificial intelligence to predict the price level that will appeal to each website visitor, automatically personalizing the landing page to display only the most relevant products based on price.
First impressions count and many online retailers experience high bounce rates when new visitors, attracted by high cost adverts, land on their website. Often, even though the merchant may have products available in the shopper’s desired price point, the retailer struggles to identify and present the items that would be ideal for a new visitor as they haven’t expressed their interests yet. The new Fresh Relevance Price Affinity Predictor helps solve this ‘cold start problem’ by making an informed decision, based on billions of shopping journeys, about what products (low, medium or high value) should be presented to the shopper when they visit the website for the first time.
Chief Technology Officer at Fresh Relevance, David Henderson, explains:
“Typically, when a new visitor lands on a website, the retailer knows nothing about them. However, there’s a wealth of information available, that when harnessed and analyzed in the right way, can provide a well- informed indication as to what that shopper’s price level is likely to be.”
“Through our work with the University of Portsmouth, we have developed new functionality for the Fresh Relevance platform that takes advantage of the latest artificial intelligence developments, to make these decisions in real-time.”
The availability of the Fresh Relevance Price Affinity Predictor will be welcome news for online retailers in competitive markets, and those with high new customer acquisition costs. Henderson states: “On the high-street, sales clerks can decide which products will be most attractive to a customer from the signals the shopper sends when entering the store. Now online retailers can do the same as part of their eCommerce strategy.”
The Fresh Relevance Price Affinity Predictor is available now to users of the Web Personalization module.