Abstract
This paper proposes a method to capture the purchase patterns of customers by analyzing purchase history data in time series. This type of data is analyzed conventionally with two axes of Merchandise and Customer. In this paper, we use an analytical method called “Customer Cube”, which analyze the data in three-dimensions of Merchandise, Customer, and Time axes. As a result of analyses using the Customer Cube, we have extracted three types of purchase patterns from the purchase history data on a CVS EC site.
By capturing the transitions of customer preferences based on the extracted purchase patterns, CVSs should be able to increase the efficiency of their marketing, merchandising and merchandise management activities, which eventually contributes to increase the sales on their EC sites.
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© 2004 Springer-Verlag Berlin Heidelberg
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Fukue, Y., Masayuki, K., Tsuda, K. (2004). Extracting Purchase Patterns in Convenience Store E-Commerce Market Using Customer Cube Analysis. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_71
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DOI: https://doi.org/10.1007/978-3-540-30132-5_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23318-3
Online ISBN: 978-3-540-30132-5
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