DocumentCode
1975994
Title
RFM Value and Grey Relation Based Customer Segmentation Model in the Logistics Market Segmentation
Author
Weiwen, XIONG ; Liang, CHEN ; Zhiyong, Zhang ; Zhuqiang, QIU
Author_Institution
Dept. of Logistics Eng., South China Univ. of Technol., Guangzhou, China
Volume
5
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
1298
Lastpage
1301
Abstract
In CRM (customer relationship management), the importance of a segmentation method for identifying good customers has been increasing. The paper recalls the development of domestic and foreign markets subdivision process and trends. This study presents a novel approach that combines customer targeting and customer segmentation for marketing strategies. This investigation identifies customer behavior using a recency, frequency and monetary (RFM) model and grey correlation model to evaluate proposed segmented customers. Models have taken into account the customer¿s value for enterprises and logistics services that the customers are concerned about. The AHP (Analytic Hierarchy Process) algorithm is used to computer the weights of indicators. To demonstrate the efficiency of the proposed method, this work performs an empirical study of a logistics enterprise to segment 10 customers. The result shows the way to segment customer is effective. So it is easy to find high added customers based for enterprises to develop effective marketing strategies.
Keywords
customer relationship management; grey systems; logistics; analytic hierarchy process; customer relationship management; customer segmentation; grey relation; logistics enterprise; logistics market segmentation; value relation; Algorithm design and analysis; Business; Computer science; Customer relationship management; Demography; Frequency estimation; Logistics; Marketing and sales; Psychology; Software engineering; AHP; RFM value model; customer segmentation; grey relation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.79
Filename
4723147
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