Typically marketing managers select the target group on the basis of their experiences and subjective opinions. Recent information technologies such as data warehouse, data mining and system integration help analyze and cluster customers automatically. However, customers clustered by these tools may not be consistent with the original target group. It is thus necessary to compare and analyze the gap between the target group and clustered customer group. Therefore, it is important to manage the customer strategy in a continuous fashion. This thesis proposes a customer segmentation methodology for managing customer relationship continuously. This methodology emphasizes gap analysis between the first target group and the clustered group. The methodology consists of 3 phases: (i) understanding of potential customer, (ii) acquisition of the customer information and (iii) management of customer relationship. Finally, this methodology is applied to a large chemical company to illustrate its usefulness.
