Integrating intelligent systems into marketing to support market segmentation decisions

For the last 50 years market segmentation has been considered to be a key concept in marketing strategy. As a means of tackling market heterogeneity, the underlying logic and managerial rationale for market segmentation is well established in the marketing literature. However, there is evidence to suggest that attempts by organizations to classify customers into distinct segments for whom product or services can be specifically tailored are proving to be difficult to implement in practice. As the business environment in which many organizations operate becomes increasingly uncertain and highly competitive, greater importance is now being attached to marketing knowledge. The purpose of this paper is to highlight market segmentation problems as a relevant area for a greater level of engagement of intelligent systems academic researchers and practitioners with their counterparts within the marketing discipline, in order to explore how data mining approaches can assist marketers in gaining valuable insights into patterns of consumer behaviour, which can then be used to inform market segmentation decision-making. Since the application of data mining within the marketing domain is only in its infancy, a research agenda is proposed to encourage greater interdisciplinary collaboration between information systems and marketing so that data mining can more noticeably enter the repertoire of analytical techniques being employed for segmentation. Copyright © 2007 John Wiley & Sons, Ltd.