Abstract
RFID data obtained from customers’ movements using radio-frequency identification (RFID) tags contain valuable information for marketing, such as shopping trip time and distance as well as the number of shelf visits. Customers’ purchasing behavior and their in-store movements can be analyzed not only by using RFID data, but also by combining it with point of sales (POS) data. In this paper, we propose an index called customer potential value (CPV), which considers customers’ potential for purchasing products using association rules and visited shelves, by analyzing the RFID and POS data. Finally, we use CPV for a purchase prediction of products and a method of customers’ segmentation of a sales promotion.
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Nakahara, T., Yada, K. (2011). Extraction of Customer Potential Value Using Unpurchased Items and In-Store Movements. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23854-3_31
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DOI: https://doi.org/10.1007/978-3-642-23854-3_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23853-6
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