Personalized Pricing and Quality Differentiation

We develop an analytical framework to investigate the competitive implications of personalized pricing technologies (PP). These technologies enable first-degree price discrimination: firms charge different prices to different consumers, based on their willingness to pay. We first show that, even though a monopolist makes a higher profit with PP, its optimal quality is the same with or without PP. Next, we show that in a duopoly setting, personalized pricing adds value only if it is associated with product differentiation. We then consider a model of vertical product differentiation, and show how personalized pricing on the Internet affects firms' choices of quality differentiation in a competitive scenario. There are two equilibria. We find that, when the PP firm has a high quality both firms raise their qualities, relative to the uniform pricing case. Conversely, when the PP firm has low quality, both firms lower their qualities. While it is optimal for the firm adopting PP to increase product differentiation, the non-PP firm seeks to reduce differentiation by moving in closer in the quality space. Our model also points out firms' optimal pricing strategies with PP, which may be non-monotonic in consumer valuations. Depending on the convexity of the marginal cost function, we outline the incentives of firms to deploy such technologies. Our model shows it is an optimal strategy for the low quality firm to adopt PP, if the other firm does not. Regardless of whether the low quality firm has PP, the high quality firm should adopt PP only if the cost function is not too convex. Next, if both firms acquire PP, then both firms earn lower profits than in the case where neither firm has PP. Essentially, they are trapped in a prisoner's dilemma. Finally, we show that, consumer surplus is highest when both firms adopt PP. Thus, despite the threat of first degree price discrimination, personalized pricing with competing firms can lead to an overall increase in consumer welfare