顧客關係管理，被許多企業視為相當重要的管理理念，而在行銷的領域當中尤其重要。顧客關係管理的重點在於區分出不同類型的顧客，並發展特定策略與顧客互動維持良好關係。而隨著企業開始了解與顧客關係的重要性，顧客價值的想法便開始受到重視，顧客價值作為行銷衡量指標，不僅能用來評估行銷成效，並且是決策的一項輔助工具，因此，可以將顧客價值視為顧客關係管理的核心。 台灣航空業面臨外在環境變遷及同業競爭激烈的情勢，有必要將顧客所需服務納入整個體系中，建構長期的顧客關係管理。本研究考量除了原先RFM模型中的RFM三個指標之外，亦加入了旅客關係長度(Length)、搭機間隔時間(Period)，也藉由文獻收集與問卷之方式，輔以層級結構分析法，分析各項指標之相對權重值與重要性排序。本文使用某航空公司的顧客基本資料、搭乘歷史記錄及顧客交易資料做為分析依據，藉此衡量航空公司顧客之貢獻度，計算出旅客價值，並區隔不同價值的顧客群，找出對航空公司最具價值的顧客及行銷目標客群。最後，依據不同旅客群的特徵與搭機表現討論並提出管理建議。 ;Customer relationship management is regarded as a very important management concept by many enterprises, and it is especially important in the field of marketing. The focus of customer relationship management is to distinguish different types of customers and develop specific strategies to maintain good relationships with customer interactions. As companies begin to understand the importance of relationship with customers, the idea of customer value has begun to be valued. As a marketing measurement indicator, customer value can not only be used to evaluate marketing effectiveness, but also an auxiliary tool for decision making. Customer value is the core of customer relationship management. The airline industry in Taiwan is facing changes in the external environment and fierce competition in the industry. It is necessary to incorporate the services required by customers into the entire system and build long-term customer relationship management. In this study, in addition to the two RFM indicators in the original RFM model, the length of the traveler relationship and travel period were also considered. Supplemented by the Analytic Hierarchy Process method to analyze the relative weight value and importance ranking of each indicator. This article uses basic airline customer data, traveling history and customer transaction data as the analysis basis to measure the contribution of airline customers, calculate passenger value and separate customer groups of different values to find out the most valuable customers and marketing target customers. Finally, discuss and propose management suggestions based on the characteristics of different passenger groups and travel performance.
