Extraction of customer potential value using unpurchased items and in-store movements

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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. © 2011 Springer-Verlag.

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Nakahara, T., & Yada, K. (2011). Extraction of customer potential value using unpurchased items and in-store movements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6883 LNAI, pp. 295–303). https://doi.org/10.1007/978-3-642-23854-3_31

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