Intelligent decision support for the pricing of products and services in competitive consumer markets

In this paper we describe a new class of systems called intelligent tactica l decision support systems which enable firms to make superior pricing deci sions within a dynamic competitive environment. The paper outlines the uniq ue aspects of such systems in relation to commercially available systems. T hese aspects are seen to be their ability to process and use knowledge on t he one hand and information external to the organization on the other. The systems use nonlinear models, optimization, and learning algorithms to prov ide decision support capabilities for the generic price-setting problem. Th e general theme of the paper is to see the systems described within this pa per as the support tools for a generic price setting process. The descripti on of the systems start with a generic one for pricing decision support in any consumer market and is then specialized to various markets each of whic h could benefit from a specific variant of the generic pricing technology w hich has been adapted to that particular industry. The adaptations from the generic pricing system to the systems for petrol pricing, retail pricing, and telecommunications taxation, have been explained. These three examples show a variety of price-setting situations ranging from near commodity pric ing, as in the case of petrol, to pricing of very sophisticated services, a s in the case of mobile telephony. Field experiments with these systems sho w that they perform significantly better than unassisted human decision-mak ers. This is seen from controlled experiments where these systems have demo nstrated significant profit uplift when applied to the experimentation site s as compared to the "control" sites where the systems have not been applie d.