Personalized Pricing And Consumer Welfare

We study the welfare implications of personalized pricing, an extreme form of third-degree price discrimination implemented with machine learning for a large, digital firm. Using data from a unique randomized controlled pricing field experiment we train a demand model and conduct inference about the effects of personalized pricing on firm and consumer surplus. In a second experiment, we validate our predictions in the field. The initial experiment reveals unexercised market power that allows the firm to raise its price optimally, generating a 55% increase in profits. Personalized pricing improves the firm's expected posterior profits by an additional 19%, relative to the optimized uniform price, and by 86%, relative to the firm's unoptimized status quo price. Turning to welfare effects on the demand side, total consumer surplus declines 23% under personalized pricing relative to uniform pricing, and 47% relative to the firm's unoptimized status quo price. However, over 60% of consumers benefit from lower prices under personalization and total welfare can increase under standard inequity-averse welfare functions. Simulations with our demand estimates reveal a non-monotonic relationship between the granularity of the segmentation data and the total consumer surplus under personalization. These findings indicate a need for caution in the current public policy debate regarding data privacy and personalized pricing insofar as some data restrictions may not per se improve consumer welfare.

We discuss the effect of personalized pricing on profits and welfare in a Hotelling model in which consumers can simultaneously purchase from both firms. As the additional gain from the second purchase increases, personalized pricing is more likely to harm (resp., benefit) consumers (resp., firms). If the additional gain is interme- diate, personalized pricing improves consumer welfare and firms' profits, contrasting with the standard result: personalized pricing benefits consumers but harms firms. When firms can choose one of the pricing policies: uniform or personalized, both choose uniform (resp., personalized) pricing under some parameters (resp., in any case); multiple equilibria can co-exist.

This paper assesses the welfare e⁄ects of rms ability to use data for group and personalized pricing in markets with unit ( q = 1) and multi-unit demand consumers ( q > 1). The disutility cost of not consuming the ideal good is a function of units purchased and can increase at a decreasing rate 2 [0 ; 1] as consumption increases (is the elasticity of the disutility cost with respect to q ): Group pricing (GP) and personalized pricing (PP) are compared to uniform pricing (UP). GP always boosts pro ts at the expense of consumers. When = 0 ; PP reduces industry pro ts and boosts consumer welfare. The same happens when q is low and/or is su¢ ciently high. In contrast, if heterogeneity in demand is su¢ ciently high and is su¢ ciently low, PP can enhance pro ts at the expense of consumer welfare.

A concern central to the economics of privacy is that firms may use consumer data to price discriminate. A common response is that consumers should have control over their data and the ability to choose how firms access it. Since firms draw inferences based on both the data seen as well as the consumer's disclosure choices, the strategic implications of this proposal are unclear. We investigate whether such measures improve consumer welfare in monopolistic and competitive environments. We find that consumer control can guarantee gains for every consumer type relative to both perfect price discrimination and no personalized pricing. This result is driven by two ideas. First, consumers can use disclosure to amplify competition between firms. Second, consumers can share information that induces a seller--even a monopolist--to make price concessions. Furthermore, whether consumer control improves consumer surplus depends on both the technology of disclosure and the competitiveness of the marketplace. In a competitive market, simple disclosure technologies such as "track / do-not-track" suffice for guaranteeing gains in consumer welfare. However, in a monopolistic market, welfare gains require richer forms of disclosure technology whereby consumers can decide how much information they would like to convey.

Data-driven AI pricing algorithms in on-line markets collect consumer information and use it in their pricing technologies. In the simplest symmetric Hotellingís model such technologies reduce prices and proÖts. We extend Hotellingís model with vertically di§erentiated products, cost asymmetries and arbitrary adjustment costs. We provide a characterization of competition in personalized pricing: Sellers compete in o§ering consumer surplus, personalized prices are constrained monopoly prices and social welfare is maximal. For linear adjustment costs, adopting personalized pricing technology is a dominant strategy for both sellers. We derive conditions under which the most effi cient seller increases her proÖt through personalized pricing. While aggregate consumer surplus increases, consumers with high switching costs may be hurt. Finally, we discuss several extensions of our approach such as oligopoly.

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.

Personalized pricing has become a reality through digitization. We examine firms' incentives to adopt one of the three pricing schemes: uniform, personalized, or group pricing in a Hotelling duopoly model. There are two types of consumer groups that are heterogeneous in their mismatch costs. We show that both firms employ personalized pricing in equilibrium regardless of the heterogeneity of consumer groups. If the consumer groups' heterogeneity is significant, the profits are higher when both firms use personalized pricing than when they employ uniform pricing; otherwise, the latter profits are higher than the former. Profits are highest when firms employ group pricing among the three cases. The ranking of consumer welfare among the three cases is opposite to that of profits.

Problem definition: Firms heavily invest in big-data technologies to collect consumer data and infer consumer preferences for price discrimination. However, consumers can use technological devices to manipulate their data and fool firms to obtain better deals. We examine how a firm invests in collecting consumer data and makes pricing decisions and whether it should disclose its scope of data collection to consumers who can manipulate their data.Methodology/results: We develop a game-theoretic model to consider a market in which a firm caters to consumers with heterogeneous preferences for a product. The firm collects consumer data to identify their types and issue an individualized price, whereas consumers can incur a cost to manipulate data and mimic the other type. We find that when the firm does not disclose its scope of data collection to consumers, it collects more consumer data. When the firm discloses its scope of data collection, it reduces data collection even when collecting more data is costless. The optimal scope of data collection increases when it is more costly for consumers to manipulate data but decreases when consumer demand becomes more heterogeneous. Moreover, a lower cost for consumers to manipulate data can be detrimental to both the firm and consumers. Lastly, disclosure of data collection scope increases firm profit, consumer surplus, and social welfare. Managerial implications: Our findings suggest that a firm should adjust its scope of data collection and prices based on whether the firm discloses the data collection scope, consumers' manipulation cost, and demand heterogeneity. Public policies should require firms to disclose their data collection scope to increase consumer surplus and social welfare. Even without such a mandatory disclosure policy, firms should voluntarily disclose their data collection scope to increase profit. Moreover, public educational programs that train consumers to manipulate their data or raise their awareness of manipulation tools can ultimately hurt consumers and firms.

We study a duopoly model where each firm chooses personalized prices for its targeted consumers, who can be active or passive in identity management. Active consumers can bypass price discrimination and have access to the price offered to non-targeted consumers, which passive consumers cannot. When all consumers are passive, personalized pricing leads to intense competition and total industry profit lower than that under the Hoteling equilibrium. But market is always fully covered. Active consumers raise the firm's cost of serving non-targeted consumers, which softens competition. When firms have sufficiently large and non-overlapping target segments, active consumers enable firms to extract full surplus from their targeted consumers through perfect price discrimination. With active consumers, firms also choose not to serve the entire market when the commonly non-targeted market segment is small. Thus active identity management can lead to lower consumer surplus and lower social welfare. We also discuss the regulatory implications for the use of consumer information by firms as well as the implications for management.

We embed the principal-agent model in a model of spatial differentiation with correlated consumer preferences to investigate the competitive implications of personalized pricing and quality allocation (PPQ), whereby duopoly firms charge different prices and offer different qualities to different consumers, based on their willingness-to-pay. Our model sheds light on the equilibrium product-line pricing and quality schedules offered by firms, given that none, one, or both firms implement PPQ. The adoption of PPQ has three effects in our model: it enables firms to extract higher rents from loyal customers, intensifies price competition for non-loyal customers, and eliminates cannibalization from customer self-selection. Contrary to prior literature on one-to-one marketing and price discrimination, we show that even symmetric firms can avoid the well-known Prisoner's Dilemma problem when they engage in personalized pricing and quality customization. When both firms have PPQ, consumer surplus is non-monotonic in valuations such that some low valuation consumers get higher surplus than high valuation consumers. The adoption of PPQ can reduce information asymmetry, and therefore sellers offer higher quality products after the adoption of PPQ. Overall, we find that while the simultaneous adoption of PPQ generally improves total social welfare and firm profits, it decreases total consumer surplus.