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2012 (Vol. 4, Issue: 23)
Article Information:

Using Data Mining Techniques to Increase Efficiency of Customer Relationship Management Process

Mohammad Behrouzian Nejad, Ebrahim Behrouzian Nejad and Ali Karami
Corresponding Author:  Mohammad Behrouzian Nejad 

Key words:  Attract customers , customer retention, data mining, CRM, , ,
Vol. 4 , (23): 5010-5015
Submitted Accepted Published
February 22, 2012 July 02, 2012 December 01, 2012

Recently the Customer Relationship Management (CRM) has been achieved an increasing popularity in business management. CRM includes all the steps which an organization employs to create and establish beneficial relationships with the customers. Using technologies such as data warehousing and data mining CRM can be introduced as a new area where companies can gain the competitive advantage. Via CRM system a company can improve its processes to deliver better service at a lower cost. By use of data mining techniques, companies can extract hidden information of the customers from large databases. So, organizations can determine the value of customers and predict their future behavior and requirements. Data mining tools can answer business questions which were time-consuming to track in the past. We believe that it is possible to improve CRM efficiency, to have an effective and rapid response to customer needs, by integrating CRM and data mining techniques. In this study we investigate major concepts of CRM and data mining. Also we introduce our idea to employ data mining techniques in CRM. This study show that using data mining techniques in CRM will improve CRM's efficiency and provide a better prediction ability to companies, organizations and industries to achieve more Profitability.
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  Cite this Reference:
Mohammad Behrouzian Nejad, Ebrahim Behrouzian Nejad and Ali Karami, 2012. Using Data Mining Techniques to Increase Efficiency of Customer Relationship Management Process.  Research Journal of Applied Sciences, Engineering and Technology, 4(23): 5010-5015.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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