An Efficient CRM-Data Mining Framework for the Prediction of Customer Behaviour

T. Femina Bahari · M. Sudheep Elayidom

118 citations0/0 files storedProcedia Computer Science

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Customer churn and segmentation Online Learning and Analytics Data Mining and Machine Learning Applications

Abstract

CRM-data mining framework establishes close customer relationships and manages relationship between organizations and customers in today's advanced world of businesses. Data mining has gained popularity in various CRM applications in recent years and classification model is an important data mining technique useful in the field. The model is used to predict the behaviour of customers to enhance the decision-making processes for retaining valued customers. An efficient CRM-data mining framework is proposed in this paper and two classification models, Naïve Bayes and Neural Networks are studied to show that the accuracy of Neural Network is comparatively better.

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References

2008Application of data mining techniques in customer relationship management: A literature review and classification 2004Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management 2014A data-driven approach to predict the success of bank telemarketing 2006Decision Support and Business Intelligence Systems 1999Building Data Mining Applications for CRM 2000Accelerating Customer Relationships: Using Crm and Relationship Technologies 2005Customer relationship management research (1992‐2002)2011Using data mining for bank direct marketing: an application of the CRISP-DM methodology

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