| Summary: | 碩士 === 國立高雄餐旅學院 === 旅遊管理研究所 === 94 === As business in domestic flights will decline following the launch of the high-speed railway, airline managers have been seeking the solution to maintain the customers now they have. It is said, corporate success depends on an organization’s ability to build and maintain loyal and valued customers. As the result of it, airline managers should make their marketing segment more efficient base on customer value.
With the growth of the information technology, enterprises nowadays could extract valid, previously unknown, comprehensible information from their large databases, to transform their data into profitable knowledge by using data mining technique. This research focuses on the study of domestic airline in Taiwan. We extracted customers’ flight record from their frequent flyer program by using RFM model to make the cluster efficiently. C4.5 Decision Tree is used as a data mining tool to find out the classified rule to indicate the customer behavior. Strategies building according to customer segment and characteristics will also be illustrated.
The result indicated that the age of customers, sex, location of their residence, occupation, and their mileage accounts came out as characteristics of customers in current value. In the potential value analysis, the age of customers, location of their residence, mileage accounts, and seasonal reason are revealed as the most important criteria. The proposed approach for mining the characteristics of valued customers can assist airline managers in developing better marketing strategies and using them to make crucial business decisions.
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