  In this paper we consider the problem of pricing multiple differentiated
products. This is challenging as a price change in one product, not only
changes the demand of that particular product, but also the demand for the
other products. To address this problem, customer choice models have recently
been introduced as these are capable of describing customer choice behavior
across differentiated products. In the present paper the objective is to obtain
the revenue-maximizing prices when the customer's decision making process is
modelled according to a particular customer choice model, namely the mixed
logit model. The main advantage of using the mixed logit model, also known as
the random coefficients logit model, for this purpose is its flexibility. In
the single-product case we establish log-concavity of the optimization problem
under certain regularity conditions. In addition, in the multi-product case, we
present the results of our extensive numerical experiments. These suggest that
the mixed logit model, by taking unobserved customer heterogeneity and flexible
substitution patterns into account, can significantly improve the attainable
revenue.
