An analytical approach to bundling in the presence of customer transition effects

Service product bundling is a widespread practice in current e-commerce environment. While many studies have examined optimal bundling and pricing in a static time domain, there has been a lack of attention to the dynamic nature of customer transition among bundles and the consequent long-term strategy. This paper considers subscription-based service bundling problem. In this context, an existing customer can choose the same bundle or switch to another bundle, whereas a new customer can adopt any of the bundles that are being offered. An analytical model that explicitly captures the customer transition over multiple time periods is developed using a dynamic systems approach. Using this model, we analyze the effect of adoption, retention, and switching simultaneously on optimal bundle configuration and pricing. We discuss several managerial insights, along with numerical examples and validating simulations, which are relevant to bundling strategy. We provide analytical results which enable an effective and efficient decision support tool to predict future demand stream for different bundles. We present a monotonicity property for the optimality condition which significantly reduces the computational burden.