The Impact of Big Data on Dynamic Personalized Pricing: Theory and Evidence

Project Outcomes Statement

Technologies that exist today allow firms to identify and track individual customers online. The possibility for firms to engage in personalized pricing have dramatically expanded with the advent of large datasets (Big Data) on consumers' individual characteristics, purchasing, and web-browsing behavior together with improved artificial intelligence (AI) techniques and the increasing role of customer feedback through social media. One concern about these developments is that firms in online markets with access to granular sensitive information about individual consumers may exploit this advantage through advanced algorithms to discriminate across consumers, charging higher prices to those who are identified to have a higher demand for their products. This project investigates whether such personalized pricing will be harmful or beneficial to consumers when competing firms have access to consumers' data.

The project first develops a dynamic model of competitive price discrimination in the presence of rich information that enables firms to implement sophisticated pricing strategies. The research demonstrates that, unlike in a monopoly setting, when competing firms can offer personalized prices, novel forms of inefficiencies can arise. Hence, new types of policy interventions to restore efficiency may be appropriate. The project shows that as long as multiple firms have access to a given consumer's data for the same product, competition between firms can make consumers better off than if no firm had access to such data and firms charged the same prices to all of their consumers. The project then applies the developed model to the online sales of smartphones and tablets to quantify how personalized pricing could affect this market. The research shows that consumers who have strong preferences for particular brands are made worse off through personalized pricing but consumers without strong preferences are made better off. On the whole, the research finds that competitive personalized pricing can benefit the average consumer.

This research has been presented to academic audiences at universities and conferences throughout the world, as well as at federal agencies, such as the Federal Communications Commission. Through this research project, a number of graduate students received mentoring and training.