Implementation of Clustering Technique Based RFM Analysis for Customer Behaviour in Online Transactions

Ananthi Sheshasaayee · L. Logeshwari

14 citations0/0 files storedInternational Conference on Trends in Electronics and Informatics (ICOEI)

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Customer churn and segmentation Customer Service Quality and Loyalty Data Mining and Machine Learning Applications

Abstract

The process of CRM's own business aptitude for integrated information storage, acquisition and decision support is to deliver adapted customer services, which qualifies to analyse customer representatives and classify customer data to sole their needs. This information is very helpful to promote greater customer satisfaction and retention. But nowadays CRM Segmentation models are outdated and deficient because of the excessive and noisy data set. In this paper, a proposed and new feature selection method using some efficient data mining techniques to resolve the customer data set according to relevant features for data quality are discussed along with the recital segmentation and RFM analysis.

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References

1995Optimal Selection for Direct Mail 2008Classifying the segmentation of customer value via RFM model and RS theory 2008Database Marketing: Analyzing and Managing Customers 1998On the Heterogeneity of Demand 2009Can governance and regulatory control ensure private higher education as business or public goods in Bangladesh 2009The impact of introducing a business marketing approach to education: A study on private HE in Bangladesh

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