Theory of due repurchase : gaining more from using less : a thesis presented in partial fulfilment of the requirements for the degree of Master of Business Studies in Marketing at Massey University, Albany, New Zealand

Abstract

The aim of the thesis is to enhance the current knowledge on repurchase behaviour and provide a model that enables marketing practitioners to ‘gain more from using less’ through reallocating their resources and investing more in underutilised customer data. This is because producing the desired customer response using the least costly marketing actions is the key to success in today’s increasingly competitive marketplace. Although models predicting repurchase behaviour in non-contractual settings exist, their predictive and explanatory performances are poor. None of these existing models considers the roles of purchase quantity (PQ) and homogeneity of interpurchase times (IPTs) in predicting repurchase behaviour. Hence, Theory of Due Repurchase is developed in this thesis and suggests that the customer’s next purchase is highly expected under three repurchase conditions, which are that the customer is 1) a frequent shopper; 2) has upward-trending PQs; and 3) has homogeneous IPTs. These three variables are not only expected to be strong predictors of repurchase behaviour, but also correctly classify more customers than existing behavioural models, including recency, frequency and monetary value (RFM). Using a transaction dataset available in the literature, six studies were conducted to empirically test the Theory of Due Repurchase, examine its predictive accuracy and replicate the findings. The results support all of the hypotheses, developed as part of the conceptual model, and replicate the findings. Theory of Due Repurchase correctly classifies over 88% of customers across four samples, improving the current level of accuracy in predicting repurchase behaviour by approximately 19 percentage points. The thesis provides a number of academic and managerial insights on effective targeting.