A Purchasing Sequences Data Mining Method for Customer Segmentation

Author

Wang, Hai ; Wang, Shouhong

Author_Institution

Sobey Sch. of Bus., Saint Mary´´s Univ., Halifax, NS

fYear

2006

fDate

21-23 June 2006

Firstpage

883

Lastpage

886

Abstract

Purchasing behavior serves a base for online customer segmentation. Online purchasing behavior is characterized by purchasing sequences. This paper reviews the existing three major techniques of sequence data analysis, and discusses their limitations in online purchasing sequences analysis for customer segmentation. The study proposes a new data mining method for online customer segmentation, and applies this method for an online nutrition product store. The data mining results indicate that the proposed data mining method is novel and effective for online customer segmentation

Keywords

consumer behaviour; data analysis; data mining; purchasing; retail data processing; data mining method; online customer segmentation; online nutrition product store; online purchasing behavior; purchasing sequences; sequence data analysis; DNA; Data analysis; Data mining; Demography; History; Organizational aspects; Pattern analysis; Sequences; Time measurement; Time series analysis; Customer Segmentation; Data Mining; Sequence Data Mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Service Operations and Logistics, and Informatics, 2006. SOLI '06. IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

1-4244-0317-0

Electronic_ISBN

1-4244-0318-9

Type

conf

DOI

10.1109/SOLI.2006.329026

Filename

4125701