Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty

Authors:
Seyed Mohammad Seyed Hosseini;Anahita Maleki;Mohammad Reza Gholamian
Affiliations:
Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran;Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran;Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

Citing 4
Cited 7

Integrating AHP and data mining for product recommendation based on customer lifetime value

Information and Management
Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques
Classifying the segmentation of customer value via RFM model and RS theory

Expert Systems with Applications: An International Journal
Segmentation of stock trading customers according to potential value

Expert Systems with Applications: An International Journal

Customer portfolio analysis using the SOM

International Journal of Business Information Systems
A case study of applying LRFM model in market segmentation of a children's dental clinic

Expert Systems with Applications: An International Journal
Segmenting customers by transaction data with concept hierarchy

Expert Systems with Applications: An International Journal
CRM strategies for a small-sized online shopping mall based on association rules and sequential patterns

Expert Systems with Applications: An International Journal
Including spatial interdependence in customer acquisition models: A cross-category comparison

Expert Systems with Applications: An International Journal
Behavior scoring model for coalition loyalty programs by using summary variables of transaction data

Expert Systems with Applications: An International Journal
A service oriented architecture to provide data mining services for non-expert data miners

Decision Support Systems

Quantified Score

Hi-index	12.06

Visualization

Abstract

Data mining (DM) methodology has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the data used by researchers. This study has proposed a new procedure, based on expanded RFM model by including one additional parameter, joining WRFM-based method to K-means algorithm applied in DM with K-optimum according to Davies-Bouldin Index, and then classifying customer product loyalty in under B2B concept. The developed methodology has been implemented for SAPCO Co. in Iran. The result shows a tremendous capability to the firm to assess his customer loyalty in marketing strategy designed by this company in comparing with random selection commonly used by most companies in Iran.