Authors : Mohsen Sadegh Amal Nik and Hamed Manshadian
Abstract: Since, air transport organizations are associated with customers directly, implementation of an accurate and appropriate customer relationship management would seem essential for them. Segmenting customers based on their value is one of the issues which is challenging in this field nowadays and many customer-oriented organizations are interested in calculating customer value and segmenting customers based on their value so that they can have a true understanding of customers. In this study, a framework is proposed to determine customer value regarding airline transport organizations considering their lifetime and potential value. Moreover, some strategies are discussed for segmenting them using data mining. A criterion is suggested for obtaining customer value considering behavioral nature of airline passengers and their traveling motives which are named business and leisure incentive in literature as well as customers’ previous purchases behavioral nature using LRFM Model. For weighing parameters of both models AHP technique is implemented. After that, k-mean algorithm is used to cluster customers based on their value. Eventually after coming up with a conceptual model for segmenting customers based on their lifetime and potential value, some customer attraction and retention strategies are proposed.
Mohsen Sadegh Amal Nik and Hamed Manshadian, 2016. A Segmentation Framework for Airlines’ Passengers Based on their Value Using Data Mining. International Business Management, 10: 898-907.