Title :
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
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;
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
DOI :
10.1109/SOLI.2006.329026
