Computing technology has changed the way firms set prices, with data and calculations replacing guesswork and rules of thumb in many industries. The continued evolution of algorithmic pricing methods has opened the door to personalized pricing, where consumers are quoted different prices based on their own individual data. Public concern about this still-developing technology has grown, causing federal agencies and state legislatures to take notice.
Many worry that firms will be able to determine the maximum amount each customer is willing to pay for an item and set personalized prices accordingly. In a particularly troubling version of this scenario, a firm might identify a consumer’s urgent or desperate need and exploit it by jacking up prices.
But while these strategies are becoming technically feasible in some settings, they remain strikingly absent in the real world. Instead, the most widespread and established current use of personalized pricing is the opposite of the targeted price-gouging many imagine. Through installed apps, membership agreements, and subscriptions, large retailers use repeat-customer data to offer extra discounts on products they are likely to demand.
Depending on how and where it is employed, personalized pricing can either enhance competition and consumer welfare, or, at least in theory, harm consumers through deception and higher prices. Pro-consumer outcomes arise in healthy markets where sellers compete vigorously, and consumers are well informed about how their data is used. This distinction should caution policymakers eager to ban or tightly control personalized pricing, but does not mean the potential for exploitation should be ignored. The rapid, uncertain development of artificial intelligence (AI) suggests focusing more attention on settings where competition or transparency is lacking.
Competition leads to personalized discounting
The only personalized pricing strategy that observers generally agree to be in current widespread use is personalized discounting. Retailers such as CVS, Kroger, and Amazon use consumers’ shopping histories to select discounts and other offers consumers are likely to find compelling. Firms access these shopping histories through relationships with consumers developed over time, and disclose the strategies through membership agreements, app downloads, and subscriptions.
These uses of personalized pricing are popular with consumers, as evidenced by the 90 million and 200 million members that CVS and Amazon respectively report in their loyalty programs. These firms emphasize that they only use personal customer data to discount prices, not to raise prices above a baseline level. This distinction between discounting and raising prices is a useful rule of thumb for desirable uses of the technology, but it is important to understand why these firms choose to discount the products repeat customers most want rather than raise their prices.
The most important factor determining whether personalized pricing benefits consumers is the presence of robust competition. While the large retailers discussed above have some market power, it is difficult to imagine any firm other than a pure and protected monopoly sustaining a strategy in which prices are set at or near the highest amount individual consumers are willing to pay. If any firm outside a protected monopoly charged prices far above the level needed to earn an ordinary profit, competitors would have opportunities to offer prices low enough to gain substantial market share but still high enough to profit.
Many of the troubling hypothetical scenarios proposed by opponents of personalized pricing focus on what is or may soon become technically feasible, but neglect the disciplining forces of competition. In an August 2026 proposed policy statement, the Federal Trade Commission (FTC) listed several potential exploitative applications, including, “a hotel charging a higher price to a consumer on the basis of data personal to that consumer leading the hotel to believe that the consumer is traveling for a funeral or some other can’t-miss personal business.” But consider the opportunity such a strategy would create for other hotels to profitably undercut their competitor. They could easily win this customer’s business by offering a lower rate, increasing their own profit. Consumers’ ability to comparison shop for hotels across multiple platforms would make opportunities to undercut exorbitant prices even more immediately lucrative, and if the offending hotel tried to sustain the strategy, it might even create opportunities for competitors to advertise discounts.
Personalized pricing strategies that raise prices to the estimated maximum each consumer will pay become even less feasible if a retailer attempted to scale this strategy across products and customers; in a 2024 letter to Kroger, Sen. Elizabeth Warren (D-Mass.) and then-Sen. Bob Casey (D-Penn.) expressed concerns that the supermarket chain would use existing technology to do just that. At issue were in-store electronic shelf labels (ESLs), created in a partnership with Microsoft, that the company used to collect data and enable market-wide dynamic pricing (where the uniform price charged to consumers can be changed without physically relabeling goods on shelves).
While the senators did not allege Kroger used the technology for personalized pricing, they expressed concerns that the installed ESLs “may enable Kroger to gather data on customers to determine how much price hiking they can tolerate and then present each customer with personalized price tags at the grocery shelf.”
Like the FTC, the senators focused on strategies made possible by technology, but that would realistically be foreclosed by market competition. If a major grocery chain tried to employ and sustain this strategy at any meaningful scale, it would create highly profitable opportunities for competitors (both brick-and-mortar and online) to undercut prices and advertise heavily. If such a grocery store were in a remote area, these high prices could attract new competitors. The only way a retailer could charge so many consumers high personalized prices is if it were a heavily protected monopoly facing near-zero competition and extremely high barriers to entry for other firms. Such a pure monopolist would likely already charge exorbitant prices to all consumers and quickly attract scrutiny from antitrust authorities.
These realities suggest that new laws banning or highly restricting personalized pricing aren’t necessary. As in other cases where firms exploit market power, targeted antitrust enforcement is likely to protect consumers against such possibilities, however remote.
The importance of well-informed consumers
Well-informed consumers are another important component of functioning markets. Harmful outcomes can emerge when consumers have less or incorrect information than the firms with whom they transact. The free flow of information about how personal data turns into prices allows consumers to make more informed decisions about where to shop. Consider again the case of a grocery store attempting to charge customers their maximum willingness to pay for items. High prices alone would likely push consumers to other stores, but knowing why those prices were so high would more quickly show consumers that competitors offer better deals.
Informative disclosures about personalized pricing are therefore important for positive market outcomes. The grocery and drugstore apps discussed above make this information clear. CVS offers members of its ExtraCare program “customized” offers and discounts through emails, text messages, and its shopping app. In its privacy policy, the firm lists the data it may collect, including demographics, shopping history, and browser cookies. The result is personalized discounts, both storewide and on specific products a consumer is likely to purchase. Kroger discloses that it uses similar customer data to provide “ways to save on items you buy most often or that you might like based on your past interests.”
The FTC notes in a recent policy statement that it lacks Congressional authority to make sweeping prohibitions on personalized pricing, but that it “intends to enforce the law aggressively against any deceptive or unfair personalized pricing practices that violate Section 5 of the FTC Act or any other law enforced by the Commission.” Nonetheless, providing consumers with clear ways to know how their data is used is an important step in building public trust and pushing back against overly prescriptive new laws or regulations.
Legitimate concerns may also arise when firms purchase data from brokers hiding in grey or black markets. Online retailers eager to purchase such data might be able to employ strategies more hidden from consumers than highly visible big-box retailers.
An earlier FTC statement, released at the end of the Biden presidency, highlights these possibilities but provides no specific examples. The FTC conducted research on data brokers, but due to a combination of incomplete information and legal restrictions, was forced to aggregate and anonymize its results. All of the brief report’s “conclusions” about personalized pricing are couched in hypothetical terms, making it difficult to determine if authorities found any concrete examples of real-world personalized pricing strategies arising from these questionable data trading practices. Authorities must spend more time studying these issues to separate fact from speculation, set standards to create public trust, and enforce any real violations of antitrust or privacy law.
Opportunities for exploitation and price-gouging have existed as long as markets themselves. Competition and informed consumers provide effective safeguards in most cases, and where they do not, modern economies have long provided rules and means to enforce them. Personalized pricing is no different. No evidence suggests that the exploitation or price-gouging many imagine has yet come to pass. If future problems arise, they will likely occur when a firm is shielded from competition or when consumer information is limited.
Personalized pricing will warrant continued attention from policymakers as AI technology continues to develop and consumers’ online data footprints continue to grow. But the same market forces that have always disciplined price-setting by firms will keep most problematic uses of the strategy in the realm of the hypothetical.