Data Mining and Customer Relationship Management for Clients Segmentation

Authors

  • Ionela Cătălina Tudorache (Zamfir) Bucharest University of Economic Studies, Economic Cybernetics and Statistics Doctoral School
  • Radu Ioan Vija Bucharest University of Economic Studies, Economic Cybernetics and Statistics Doctoral School

Keywords:

Classification, Clients, CRM, Data Mining, Segmentation

Abstract

Starting from the idea that, nowadays, data mining techniques are applied in more and more different domains, one of the most important economic domain is Customer Relationship Management. In this respect, many studies were developed, from market research studies, to clients segmentation. We use principal components analysis to extract essential information from our dataset, and to eliminate redundancy, we use Ward's hierarchical classification method and k-means algorithm to classify clients that belong to Deloitte. Analyzing over 40 of the biggest clients, our goal is to use data mining techniques for customer segmentation, in order to both identify hidden patterns in data and describe new formed classes. In this respect, the management of the company may identify classes of customers and clients value, in order to decide future campaigns, offers or communications for a specific segment. Finally, we conclude that data mining techniques can be used for clients segmentation and provide useful results for marketing, products and management departments of the company. 

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Published

2015-10-01

How to Cite

Tudorache (Zamfir), I. C., & Vija, R. I. (2015). Data Mining and Customer Relationship Management for Clients Segmentation. International Journal of Economic Practices and Theories, 5(5), 571-578. Retrieved from http://cyberknowledgeclub.org/index.php/ijept/article/view/Data_Mining_and_Customer_Relationship_Management_for_Clients_S