To meet or even exceed customers' expectations, companies are devoting substantial resources to proactively understand the relationships between their product or service offerings and the associated target customers. With the advent of advanced information technologies, firms are now able to collect and store mountains of data describing their myriad offerings and diverse customer profiles, from which they seek to derive information about their customers' needs and wants. In this paper, a five-step data-mining model integrated with attribute relevance analysis, decision-tree classification, and rules extraction is discussed. A prototype application of the approach to a large mobile phone manufacturer is given to show the effectiveness of this approach. It is seen that this data-mining model can serve as an efficient vehicle for firms not only to predict the products or services that should be provided or improved for their target customer groups, but also to identify the right customers for a specific product family or service.
Published in:
Service Systems and Service Management, 2007 International Conference on
Date of Conference: 9-11 June 2007