Bridging the Analytics Gap: Location-based Services in Brick-and-mortar Retailing

Stationary retailers have been struggling with competition from their online counterparts, a development further accelerated by the Covid pandemic. In their attempts to create engaging offline shopping experiences, physical stores face an analytics gap compared to online retailers due to limitations of data capture and time lags between analysis and managerial action. While online stores routinely capture data on user behavior on their website, stationary retailers have a limited understanding of how shoppers behave at the point-of-sale (PoS). For instance, online retailers can analyze which customers view which products, for how long, and in which order before placing them in a shopping cart, while stationary retailers are limited to analyzing cashier data (i.e., limited data capture). Additionally, online retailers can proactively target customers in the purchase process, while stationary retailers are limited to post-hoc analyses before deciding on changes (i.e., time lags). Although digitalization has enabled the success of online retailers, it also has the potential to help stationary retailers understand shopper behavior at the PoS and create an engaging service experience. Specifically, in-store shopping apps with location-based services allow retailers to track and analyze customers’ in-store movement, support the service experience (e.g., with in-store navigation and augmented reality), and target customers in real-time (e.g., delivering coupons when customers stand at a shelf). Recent studies examined the effects of location-based services based on surveys and scenario-based approaches (e.g., Pantano et al., 2018; Roggeveen and Sethuramn, 2020; Schrage et al., 2022; Van de sanden et. al., 2019), while investigations based on behavioral field data are lacking. We address this shortcoming by collaborating with two German DIY stores that have implemented location-based services. The combination of Bluetooth Low Energy beacons installed in the stores and a mobile shopping app enables localization and tracking of customers in the store, as well as delivering personalized location-based content. We are currently collecting field data, which include information on individual customers’ in-store movement, their usage of digital services (e.g., in-store product finder), and purchases. As of November 2022, more than 10,000 shopping trips have been tracked and we are preparing the data analyses. At the time of the conference, we will be able to present results regarding shopper in-store behavior, location-based services usage, and its impact on purchase behavior. Moreover, the study setting also enables us to analyze repeated store visits over time, thus allowing for examinations of loyalty effects. Overall, our study will contribute to a better understanding of how digital services can augment and enhance physical customer experiences and how offline retailers can use such technology to bridge the analytics gap.