In most microeconomics textbooks, perfect price discrimination is seen as more of a theory than an actual business method used by firms. For those who are unfamiliar with the concept, perfect price discrimination, also called first degree price discrimination, is a form of nonuniform pricing in which a firm with market power sells each unit at each consumer’s maximum willingness to pay. The obvious issue with actually administering perfect price discrimination is that it is either impossible or financially infeasible for a company to acquire perfect information about each consumer, so they are unable to set a reserve price for each potential buyer. The lack of attainability of using perfect price discrimination is slowly beginning to diminish due to technological advances in consumer purchase tracking and web browsing data. An assistant professor at Brandeis University conducted research on how using this type of data could lead to making perfect price discrimination possible, and his specific case study was with Netflix. Currently, a subscription to Netflix is set at a single price of $8.99 per month. Shiller found that without using any consumer information and sticking to a single-price monopolistic competition, an individual’s probability of subscribing is 16%. Then, when he analyzed standard demographic information such as race, age, and income, thus using more of a third degree price discrimination approach, an individual’s probability of subscribing to Netflix ranges from 6% to 30%. Finally, when Shiller observed individual web behaviors, such as website history and online shopping patterns, predicted probabilities of subscribing ranged from almost 0% to 91%. For example, those who frequently used Rotten Tomatoes or Wikipedia were almost always more likely to already have a Netflix subscription. Based on this information, nearly an entire demand curve can be derived from this information, which could allow Netflix to better target people with a higher willingness to pay, and offer lower prices to people with a lower willingness to pay, while still profiting more than beforehand. This ultimately would appropriate all potential consumer surplus into producer surplus, hence creating a higher profit, which Shiller estimates could increase 1.39% by using a near perfect price discrimination.
Of course, perfect price discrimination has its issues, especially with the inequality of who this type of price discrimination benefits. Because prices vary based on each consumer’s reserve price, the marginal revenue curve becomes the demand curve. Each consumer is paying his or her highest willingness to pay, so consumers no longer have any surplus, and producers acquire all of the surplus. This means that consumers don’t acquire any monetary gain because the price that is sold to them isn’t less than their highest willingness to pay. Although perfect price discrimination puts consumers at a disadvantage, it is efficient in the sense that there is no dead weight loss, unlike a single price monopoly. Despite the fact that perfect price discrimination is the most beneficial to producers, they still opt to use group or nonlinear price discrimination because of the high transaction costs of acquiring perfect information. Even in this example, there is a potential for Netflix to be wrong about a consumer’s reservation price because although web browsing information can be very telling about a person’s spending habits, it isn’t a guarantee. Being incorrect costs a firm because either they overestimate the reservation price, so the consumer doesn’t buy the good at all, or the firm underestimates the reservation price, so the consumer acquires surplus because they have a higher willingness to pay than what was estimated. Nevertheless, the increased feasibility of acquiring consumer information is bringing perfect price discrimination farther out of the theoretical world, and more into the real world.