Abstract
To support personalized marketing, it is necessary to identify an individual customer’s true value. Various researches on customer value have conducted under the name of Customer Lifetime Value (CLV), Customer Equity, Customer Profitability, and Lifetime Value. In this paper we present issues of calculating individual customer’s lifetime value to deploy more personalized CRM activities. We propose a new method to calculate individual customer’s lifetime value dynamically. The feasibility of the suggested model is illustrated through a case study of the wireless telecommunication industry in Korea. Data mining techniques are used to predict lifetime value of a customer. Marketing implications will be discussed based on the result of individual CLV.
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