Application of data mining techniques for improving customer services

Data mining is the process of discovering interesting knowledge such as pat terns, associations, changes, anomalies and significant structures from lar ge amounts of data stored in databases. This helps analyze. understand. or even visualize the huge amounts of stored data gathered from business and s cientific applications. A number or data mining applications have emerged f or a variety of domains including marketing. banking, finance, manufacturin g and health care. In traditional customer service support. most manufacturing companies store their customer service reports, that record machine problems (or fault-con ditions) and its remedial actions (or checkpoint solutions) taken to rectif y the problems, in a customer service database. In addition. for management purposes. structured data on sales, employees and customers are also store d. As such. the customer service database serves as a repository of invalua ble information and knowledge that can be utilized to improve Customer serv ices. This paper discusses the application of data mining techniques to ext ract knowledge from a customer service database for improving customer serv ice support.