Abstract
The purpose of this study is to investigate new forms of marketing data-driven knowledge discovery in the vending machine (VM) industry. Data of shopping activities understanding were gathered and analyzed by a system technology based on a RGBD camera. An RGBD camera, already tested in retail environments, is installed in top-view configuration on a VM to gather data that are processed and embedded within a knowledge discovery project. We adopted the knowledge discovery via data analytics framework (KDDA) that was applied to a real-world VM scenario. Real-world case tests, based on more than 17.000 shoppers measured in 4 different locations, were conducted. By using this method it was possible to verify the ability of this approach to generate new forms of marketing data-driven knowledge available on the VM industry. Main novelties are: i) the application of a KDDA project to the VM industry; ii) the use of RGBD data sources for the first time for a KDDA process; iii) the contribution to the practice by supporting retailers to carry out knowledge discovery processes more effectively; iv) the real-world testing process based on 4 locations and more than 17.000 shoppers.
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Marinelli, L., Paolanti, M., Nardi, L., Gabellini, P., Frontoni, E., Gregori, G.L. (2021). Data-Driven Knowledge Discovery in Retail: Evidences from the Vending Machine’s Industry. In: Del Bimbo, A., et al. Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021. Lecture Notes in Computer Science(), vol 12662. Springer, Cham. https://doi.org/10.1007/978-3-030-68790-8_40
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