원문정보
초록
영어
The more competition among industry participants severe, the more companies try to retain their customers and acquire new customers from their competitors. To gain competitive advantage, many companies are adopting and deploying more refined and sophisticated Customer Relationship Management systems. In the marketing area, a personalized marketing paradigm has already been infiltrated into our lives. 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.
목차
1. Introduction
2. Related Works
3. A Dynamic Model for Measuring Customer Lifetime Value
3.1. Individual CLV Equation
3.2. Limiting Probability of CRD
4. A Case Study on a Wireless Telecommunication Company in Korea
4.1. Decision Variables of Individual CLV
4.2. Building the one-step transition matrix
4.3. One-step transition matrix of customer i
4.4. Reward Vector of Customer i
4.5. Lifetime Value of Customer i
4.6. Limiting Probability of Customer i
5. Marketing Implications
6. Conclusion & Further Research Directions
Acknowledgements
References