Using Data Mining in Customer Relationship Management

Only available on StudyMode
  • Download(s) : 44
  • Published : November 1, 2010
Open Document
Text Preview
Expert Systems with Applications 37 (2010) 5259–5264

Contents lists available at ScienceDirect

Expert Systems with Applications
journal homepage:

Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty Seyed Mohammad Seyed Hosseini *, Anahita Maleki, Mohammad Reza Gholamian Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran

a r t i c l e

i n f o

a b s t r a c t
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. Ó 2009 Elsevier Ltd. All rights reserved.

Keywords: Customer relationship management Customer loyalty K-Means algorithm RFM model

1. Introduction In a B2B environment, suppliers and/or service providers usually need to understand the nature and characteristics of their customers. As customer attraction and satisfaction are the main objectives of any leading company, so the main objective of this article is to provide an effective and efficient methodology to be used for implementing the firm’s objective to the best of possible. This part mainly reviews the studies related to customer relationship management, customer loyalty, RFM model, K-means algorithm. 1.1. Customer relationship management Since the early 1980s, the concept of customer relationship management in marketing, and consists of four dimensions: customer identification, customer attraction, customer retention and customer development has gained its importance. It is difficult to find out a totally approved definition of CRM. We can describe it as a comprehensive strategy and process of acquiring, retaining and partnering with selective customers to create superior value for the company and the customer (Parvatiyar & Sheth, 2004). CRM is a comprehensive business and marketing strategy that integrates technology, process, and all business activities around the customer (Anton, 1996; Anton & Hoeck, 2002). Brown points out that CRM as ‘‘the key competitive strategy you need to stay focused on the needs of your customers and to integrate a customer* Corresponding author. Tel.: +982177240447; fax: +982177240482. E-mail addresses: (S.M.S. Hosseini), anahitamaleki@ (A. Maleki), (M.R. Gholamian). 0957-4174/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2009.12.070

facing approach throughout your organization” (Brown, 2000). Chatterjee also defines CRM as a discipline which focuses on automating and improving the business processes associated with managing customer relationships in the area of sales, management, customer service, and support (Chatterjee, 2000). According to Feinberg and Kadam, profits increase by 25–80% when customer retention rates increase by five points (Feinberg & Kadam, 2002). CRM projects often fail and only about 40% of CRM implementations are successful (Feinberg & Trotter, 2001). 1.2. Customer loyalty Creating a loyal B2B customer base is not only about maintaining numbers of customer overtime, but it is creating the relationship with business customers to encourage their future purchase and level of advocacy. Equipped with the knowledge of their business customers’ loyalty levels, a supplier will be able to figure how their endeavors to...
tracking img