How in-store sensor technologies can help retailers to understand their customers: overview on two decades of research

Abstract

To compete with e-commerce, retailers are increasingly integrating smart technologies into their offline retail environment. This enables retailers to analyze their customers and provide them with a personalized shopping experience. However, research to date has mainly focused on the customer rather than the retailer. Building on a semi-systematic review of 75 studies using sensor technologies in retail environments between 2001 and 2021, this paper facilitates future research on the selection and combination of sensor technologies for in-store customer analysis from a retailer’s perspective. The literature was analyzed in terms of the technology used, the raw data collected, and the interpretation of the data. The results show that technologies were primarily used to gain insights into customers’ physical behavior, while few studies attempted to identify the customer or examine customers’ emotions. The identified studies rarely combined multiple technologies. Based on the analysis, this study provides recommendations for selecting and combining sensor technologies in stores. Current approaches to support technology selection take a broad perspective and compare entire store technology concepts, such as smart shelving or smart shopping carts, rather than basic sensor technologies. The findings are relevant to both research and retail practice.

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