We develop a consumer response model to evaluate and plan pricing and promotions in durable good markets. We discuss its implementation in the US automotive industry, which “spends” about $50 billion each year in price promotions. The approach is based on a random effects multinomial nested logit model of product and transaction-type choice. Consumers differ in their overall price sensitivity as well as in their relative sensitivity to alternative pricing instruments which has to be taken into account to design effective pricing programs. We estimate the model using Hierarchical Bayes methods to capture response heterogeneity at the local market level. We illustrate the model through an empirical application to a sample of data drawn from J.D. Power transaction records.