Title: Application of data mining techniques for improving customer services

Authors: S.C.Hui, G. Jha

Addresses: Nanyang Technological University, School of Applied Science, Nanyang Avenue, 639798, Singapore. Nanyang Technological University, School of Applied Science, Nanyang Avenue, 639798, Singapore

Abstract: Data mining is the process of discovering interesting knowledge such as patterns, associations, changes, anomalies and significant structures from large amounts of data stored in databases. This helps analyse, understand, or even visualise the huge amounts of stored data gathered from business and scientific applications. A number of data mining applications have emerged for a variety of domains including marketing, banking, finance, manufacturing and health care. In traditional customer service support, most manufacturing companies store their customer service reports - that record machine problems (or fault conditions) and any remedial actions (or checkpoint solutions) taken to rectify the problems - in a customer service database. In addition, for management purposes, structured data on sales, employees and customers are also stored. As such, the customer service database serves as a repository of invaluable information and knowledge that can be utilised to improve customer services. This paper discusses the application of data mining techniques to extract knowledge from a customer service database for improving customer service support.

Keywords: data mining techniques; help desk; customer service; case-based reasoning; neural network.

DOI: 10.1504/IJCAT.2001.000261

International Journal of Computer Applications in Technology, 2001 Vol.14 No.1/2/3, pp.64-77

Published online: 15 Jul 2003 *

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