Title :
Data mining application for customer segmentation based on loyalty: An iranian food industry case study
Author :
Hajiha, Ali ; Radfar, Reza ; Malayeri, Samira Sarafi
Author_Institution :
Dept. of Ind. Manage., Islamic Azad Univ., Tehran, Iran
Abstract :
Data Mining (DM) is a powerful new technique to help companies discover the patterns and trends in their customers´ preferences. It is also a well-known tool for customer relationship management (CRM). Data mining methodology has made a tremendous contribution for researchers wanting to extract hidden knowledge and information. This study has proposed a new procedure, based on an expanded RFM model, by including two additional parameters D and C. It constructs a model for clustering customer value based on RFMDC attributes and K-means algorithm. We evaluate the result and suggest suitable behavior policies for each cluster. The developed methodology has been implemented for Kalleh dairy company in Iran to illustrate the proposed procedure.
Keywords :
customer satisfaction; data mining; food processing industry; pattern clustering; production engineering computing; Iranian food industry; K-means algorithm; Kalleh dairy company; customer loyalty; customer preferences; customer relationship management; customer segmentation; data mining application; expanded RFM model; hidden knowledge extraction; pattern discovery; Algorithm design and analysis; Clustering algorithms; Companies; Customer relationship management; Data mining; Databases; Customer loyalty; Customer relationship management; Data mining; K-means algorithm; RFM model;
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-0740-7
Electronic_ISBN :
2157-3611
DOI :
10.1109/IEEM.2011.6117968
