Hyper-Personalized Recommendations
The key to effective cross- and upselling are recommendations that are highly relevant to the respective customer. Which means: personalized ones. Find out how a Scan & Go app can help gather the relevant information and display these recommendations in an optimal way.
Hyper-personalized recommendations, based on past shopping behavior, have been a missing component in brick-and-mortar retail, even though they have been driving e-commerce revenues for a long time. While the big online retailers like Amazon are already famous for their recommendation systems, designed for giving users personalized suggestions, this feature has yet to be devised for offline retail.
Or so you might think.
But ever since the first Scan & Go apps were installed on customers’ smartphones, the comprehensive personalization of featured products has become accessible to retailers without an online presence as well. Including all the convenient components known from online shopping.
Collecting master data for improved recommendations
All the data necessary – from the search history in the app, products added to the basket, previous purchases, social media activity, or current location in the retail store – is being collected in real-time by the Scan & Go app.
Once these in-store analytics are available, targeting promotions and individual recommendations accordingly, and increasing sales revenue becomes an easy feat. And the strategy obviously works, since customers using Scan & Go tend to spend 10% more money per shopping trip, when compared to shoppers using a regular cash desk, as researchers of the University of St. Galleni have found.
Moreover, since the recommendations and relevant promotions can be displayed right there on customers’ mobile devices during their shopping trip – perhaps even while they are located in the respective aisle – the timing is perfect, and the experience becomes an even more personalized one.