Strategy:

To increase the average check size of each food order, this QSR deployed a Trending Now recommendation strategy to showcase the most popular products at each brick & mortar location. The recommendation took into account real-time data from each location to increase product discovery and drive up the check size of each customer.

Hypothesis:

Product recommendations based on real-time data allow restaurants to respond swiftly and automatically to contextual events on a location-by-location basis. For example, if Store A was located near a soccer field and children began eating there post-match, items like kids’ meals and ice cream would trend at that location and encourage more families in the vicinity to shop. At the same time, Store B around the corner, located close to an office building, might have items like coffee and muffins trending to encourage nearby workers to grab a pick-me-up. This specificity allows restaurants to more immediately meet the needs of customers, driving up product discovery and check size over time.