Background: The current study was undertaken to find out the various benefits customers perceive as accruing from being members of loyalty programs of departmental stores. The study outspreads Yi and Jeon’s (2003) work assimilated along with the diverse advantages framework advocated by Mimouni-Chaabane and Volle (2010) from the perspective of departmental stores in India. Objective: The primary aim of the current study is to find out different groups of customers based on their perception of loyalty program benefits and to identify their demographic profile. Material and methods: The scale relating to observed loyalty program benefits was authenticated in respect of Indian customers. The customers were divided into clusters based on their opinion of the benefits of loyalty programs. Further, Classification and Regression Tree (C&RT), a Machine Learning technique, was applied to find out if and how demographic characteristics have an impact on a customer’s inclination to go for a repeat purchase in a store whose loyalty program membership the customer has. Results and conclusion: Three clusters namely ‘Prospects, ‘Uncertain’ and ‘Suspects’ were identified and the profile of different clusters were enumerated to enhance the understanding, which can be utilized for making the targeting efforts of companies more effective.


Loyalty Programs; Benefits; Cluster; Demographics; Machine Learning; Classification and Regression Tree; C&RT

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