DocumentCode :
2617031
Title :
Research on customer segmentation in retailing based on clustering model
Author :
Li, Zeying
Author_Institution :
Dept. of Math & Inf. Technol., Hanshan Normal Univ., Chaozhou, China
fYear :
2011
fDate :
27-29 June 2011
Firstpage :
3437
Lastpage :
3440
Abstract :
Data mining can efficiently deal with the large number of historical and current data, from the database can find some potential, useful and valuable information for the retail stores. The paper takes a large retail supermarket as its study object, use data mining methods to retail enterprise customer segments, and then use association rules to different groups of customer and get rules about customer characteristics to make customer characteristic analysis. Finally, give some references to the supermarket´s marketing and management work.
Keywords :
consumer behaviour; customer relationship management; data mining; pattern clustering; retailing; clustering model; customer characteristic analysis; customer segmentation; data mining; retail supermarket management; retailing; supermarket marketing; Analytical models; Association rules; Data models; Databases; Information technology; Optimization; K-means; clustering analysis; customer value matrix; data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
Type :
conf
DOI :
10.1109/CSSS.2011.5974496
Filename :
5974496
Link To Document :
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