CUSTOMER MIGRATION MANAGEMENT USING CUSTOMER DATA IN TELECOM INDUSTRY

Companies have dierent sources of value. In competitive markets, customers and their relationships with a company comprise an important part of organizational value. Therefore, customer retaining is a valuable strategy that guarantees a long-term prot and success in the company. To win in today's competitive markets, com panies need to recognize their customers' requirements to predict their behavior before their rivals do. However, customer retaining only is not enough, because the dynamic nature of customers' behavior makes marketing planning inecient and ineective. Therefore, companies must continually monitor changes in customers' behavior to adapt their own marketing planning to customers' behavior. Common analyses of customers' behavior are focused on customer churn and segmentation. Another form of customer analysis, less noticed by many marketers, is the management of small changes in customers' behavior, while if it is not paid attention to, they lose a great deal of value over time, because many changes in customer's spending behavior are not primarily subject to products defects.Therefore, an important form of customer segmentation is customer migration that focuses on smaller changes in customer spending and considers customer value at dierent points in time to help companies not only stem the downward course, but also in uence upward migration earlier. There are several migration patterns. Some move from economy class to business class, and to rst class. Some move from buying one product to buying several dierent products. Some migrate by changing their lifestyle. Beyond such broad changes, companies can create superior value propositions by tailoring benets to specic subsegments to reduce not only the chance of their defects, but also to encourage customers to consolidate their spending, so that they can continue receiving benefb01ts. In this research, in order to understand the migration pattern, after introducing aspects of changes in customers' behavior, we propose new approaches for studying the changes using customer database and applying those to analyzing the customers of a subset of xed-line telecom.