The purpose of this paper is to suggest a method of selecting efficient customer service programmes and of providing relevant customer information to dealers, based on the analysis of repeat-purchase behaviour data in the automobile industry.
A recurrent event model is proposed and employed to determine which variables affect repurchasing behaviour in consumers' repurchase cycles. Unlike the conventional recurrent event model, the proposed model uses common variables for all strata, as well as stratum-specific variables.
Empirical results show that age, price difference, change in vehicle type, and marketing promotion affect the likelihood of repeat purchase. VIP service centres and repair services are effective marketing tools, and dealers should pay more attention to existing customers having certain characteristics, depending on prior purchase behaviour.
Though many customer service programmes are devised and implemented at great cost, Customer Relationship Management (CRM) data reveal that classic car-care services are the most essential. CRM can provide dealers with essential customer information that enables real purchases.
Collecting primary data on automobile purchase behaviour and customer service usage is difficult, and therefore, customer behaviour strategy is often formulated using basic principles alone. The paper proposes a method to construct a service strategy and formulate deal guidelines based on CRM data and statistical modelling.
The authors are grateful to the Editor and two anonymous referees for their helpful comments. This work was supported by the Sogang University Research Grant of 2011 (201110034.01).
Kim, J. and Suk Kim, M. (2014), "Analysis of automobile repeat-purchase behaviour on CRM", Industrial Management & Data Systems, Vol. 114 No. 7, pp. 994-1006. https://doi.org/10.1108/IMDS-01-2014-0031Download as .RIS
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