Data mining using fuzzy theory for customer relationship management

Kok Wai Wong

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

Abstract

Customer Relationship Management (CRM) initiatives have gained much attention over the past few years. Although CRM involves technology, the important success factor involves strategy. This is the strategy of building business around the customer. However, with the aid of data mining techniques, business can formulate the strategy easier. Fuzzy theory allows human expertise and decisions to be modelled more closely, thus it is suggested that it can be used in the CRM model. A case study presented in this paper has examined two area of a typical CRM model, where the decision making process can be improved by using fuzzy theory.

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References

1997Market Segmentation: Conceptual and Methodological Foundations 1978Issues and Advances in Segmentation Research 1999Building Data Mining Applications for CRM 1998Determining Segmentation in Sales Response across Consumer Purchase Behaviors 2001The Customer Differential: The Complete Guide to Implementing Customer Relationship Management

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2006Development of Fuzzy Expert System for Customer and Service Advisor Categorisation within Contact Centre Environment

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