Case study: In-store display and visual merchandising analytics

Abstract

In this project, video and advanced machine learning were used to analyse shopper behaviour in a key display area at multiple locations of a multi-billion-dollar retailer. The goal was to understand the volume of shoppers using the area, engagement with the displays, and whether the displays generated product interactions and takeaways. In addition, the system was used to design and support an aggressive testing programme to optimise the display area. Measurement answered the usage questions and revealed obvious opportunities for improvement. Structured testing revealed that the geometry of the area heavily impacted usage and engagement, that shopper flow was strongly influenced by changing the density and alignment of the features, and that there were opportunities for improving product mix and layout. As the purpose of a store is to get shoppers’ eyes and hands directly on product, the ability of product displays to attract and engage shoppers is critical to retail success. Like many aspects of physical retail, however, merchants have little visibility into the success of any given display and insufficient measurement to drive testing and improvement programmes. This case study shows how measurement and testing in display has become possible using people-counting technologies.