Title: Mining purchasing sequence data for online customer segmentation

Authors: Hai Wang, Shouhong Wang

Addresses: Sobey School of Business, Saint Mary's University, Halifax, NS, Canada. ' Charlton College of Business, University of Massachusetts Dartmouth, 285 Old Westport Road, Dartmouth, MA 02747-2300, USA

Abstract: Purchasing behaviour serves as a base for online customer segmentation. Online purchasing behaviour is characterised by purchasing sequences. This paper reviews the existing major techniques of sequence data analysis and discusses their limitations in analysing Online Purchasing Sequences (OPS) for customer segmentation. This paper presents a new data mining method for online customer segmentation and applies this method to an online nutrition product store. The data mining results indicate that the proposed data mining method is effective for online customer segmentation.

Keywords: data mining; sequence data analysis; customer segmentation; purchasing behaviour; online customers; online stores; nutrition products; online shopping.

DOI: 10.1504/IJSOI.2007.015641

International Journal of Services Operations and Informatics, 2007 Vol.2 No.4, pp.382 - 390

Published online: 06 Nov 2007 *

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