Once the mainstay of shopping and cultural exchange, many high streets increasingly struggle to compete for their customers' wallets and leisure time against digital shopping. Besides superior convenience and broader assortments, data-driven recommendations of products that fit individual customers' needs are particular assets possessed by online stores. While first recommender systems that leverage the properties of physical environments have been designed and evaluated in shopping malls, their applicability, accuracy, impact, and business value have neither been demonstrated nor evaluated in local high streets. We set out to identify and quantify the impact of geospatial recommendations on high street retail in a large German city center. Having equipped 66 local businesses with more than 120 Bluetooth Low Energy beacons and having distributed a mobile application to 400 customers, we collect geospatial data to trace customer journeys on the high street. In a field experiment, we plan to identify, analyze, and quantify the effects of recommendations in this setting. Our results will provide new data-driven insights into the accuracy, acceptance, impact, and business implications of geospatial recommendations in high street ecosystems.
Betzing, Jan Hendrik; Bartelheimer, Christian; Niemann, Marco; Berendes, C. Ingo; and Beverungen, Daniel, (2019). "QUANTIFYING THE IMPACT OF GEOSPATIAL RECOMMENDATIONS: A FIELD EXPERIMENT IN HIGH STREET RETAIL". In Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. ISBN 978-1-7336325-0-8 Research-in-Progress Papers.