This helps store associates recommend much more relevant products and services based on customers' online behaviors (search, view, compare of products, add to basket, price alert, purchase etc.) and offline purchase patterns. It’s based on an analytical data set that merges online and offline data it produces new micro segments and new profiles (above 40 years old, likes luxury, working, shopping only weekends, etc.).
Especially for the webrooming customer that is searching on the web and buying from the store the solution helps sales associate to understand what the customer looked which product, their comparisons. Sales associates are able to recommend much better based on this customer profile insight. All those make customer experience better with a higher quality service.