Discovering customer value for marketing systems: an empirical case study
本研究基于RFM模型提出FSLC模型，利用数据挖掘技术分析台湾航空旅客市场，生成关联规则以识别高价值旅客，帮助航空公司优化营销和客户关系管理系统。
Data mining technologies have been employed in a variety of business managements for discovering useful commercial knowledge or marketing model for many years. Hence, the major marketing issue for airlines is to identify and analyse valuable air travellers recently, so that airlines can attract them for enhancing the profits and growth rates. However, growth rates are always an important issue for airline industries. An empirical case of air travellers’ markets in Taiwan is implemented in this research. This research proposes a model (FSLC model, RFM model based) via the data mining technologies to discover valuable travellers for airlines. This study partitions the market of air travellers in Taiwan, and the paper generates useful association rules to find an optimised target market for dynamic marketing or CRM systems. Nevertheless, the results of this research can be applied on marketing or CRM systems of the airline industry for identifying valuable travellers. Finally, the purpose of this research is to find high-value markets for marketing or CRM systems of airlines in Taiwan, and the framework can be applied to other industries as well.