Use of Bayesian Analysis of Semi-Markov Process Models to Study Consumer Buying Behavior

SYNOPTIC ABSTRACTAnalytical techniques are developed for a combined treatment of the interpurchase-times and brand-choices of frequently purchased consumer goods, in the framework of a semi-Markov process. The inverse Gaussian distribution is used as a model for the interpurchase times. To account for heterogeneity of the consumer population, a natural conjugate prior for the model parameters is developed and the compounding distribution is fitted to panel data of toothpaste purchases. Some important summary measures are derived, including: the market share of a brand as a function of time; the long-run behavior of the interval transition probabilities and the market share; and, the distribution of the number of purchases in a given time span.