Surveillance pricing is a form of personalized dynamic pricing in which a seller uses data about an individual consumer — location, demographics, browsing history, shopping habits, or device type — to set an individualized price for the same good or service, frequently charging more where the data support an inference of higher willingness to pay. The term entered US regulatory usage through a Federal Trade Commission Section 6(b) market study opened in July 2024, and has since anchored a congressional inquiry and several state statutes.
Definition and scope
The FTC defines surveillance pricing as personalized dynamic pricing that draws on a consumer's online data to set individualized prices, "often charging higher amounts based on an inferred willingness to pay" (Source: democrats-energycommerce.house.gov). The FTC's 6(b) orders described the object of study as an opaque market in which third-party intermediaries claim to use "advanced algorithms, artificial intelligence and other technologies, along with personal information about consumers — such as their location, demographics, credit history, and browsing or shopping history — to categorize individuals and set a targeted price for a product or service" (Source: ftc.gov).
The practice is distinguished from the coordination questions treated under Algorithmic Pricing and Antitrust: surveillance pricing concerns the use of one seller's data about one buyer, rather than the pooling of competitor data across sellers. Both, however, depend on the same consumer-profiling infrastructure discussed in Three Privacy Problems AI Creates.
FTC 6(b) study
The FTC issued orders to intermediary companies in July 2024 and released initial staff findings in January 2025. Staff reported that consumer behaviors ranging from mouse movements on a webpage to items left unpurchased in an online shopping cart could be tracked and used to tailor pricing, and that some respondents could set individualized prices and discounts from granular data — the staff perspective cites a cosmetics company targeting promotions to specific skin types and skin tones, and a hypothetical in which a consumer profiled as a new parent is shown higher-priced baby thermometers first in search results. Then-chair Lina M. Khan stated that "initial staff findings show that retailers frequently use people's personal information to set targeted, tailored prices for goods and services — from a person's location and demographics, down to their mouse movements on a webpage" (Source: ftc.gov).
The staff analysis grouped the products supplied by intermediaries into price targeting tools, which set prices according to consumer behavior and market conditions; consumer segmentation and profiling tools, which categorize customers for personalized promotions; and search and product ranking tools, which customize how products appear on a site. It grouped the inputs into direct behavioral data (IP address, device type, browser and language settings, scroll depth, mouse movement), inferred data (location from IP address, purchase intent, emotional state, or price sensitivity), third-party and first-party company data, and persistent consumer profiles linked through cookies or checkout email addresses. The FTC's issue spotlight identifies consumer exploitation through pricing and promotions, privacy risks, data obfuscation, and discrimination as potential harms. The findings were characterized by the agency as preliminary and non-exhaustive (Source: mccarter.com).
Subsequent FTC leadership deprioritized continuation of the study. Chair Andrew Ferguson characterized the prior report as a "rush job," which advocates have cited as context for the shift of activity to the states, per Maryland Protection from Predatory Pricing Act.
Congressional inquiry
Energy and Commerce Committee Ranking Member Frank Pallone, Jr. (D-NJ) opened a committee inquiry into surveillance pricing in May 2026 with letters to 25 large corporations — including Albertsons, Amazon, Costco, Giant, Kroger, Target, Wegmans, and Whole Foods — asking whether they use consumers' personal data to charge different prices for the same goods, with particular attention to online shopping and a response date of May 26, 2026 (Source: democrats-energycommerce.house.gov).
On August 12, 2026 Pallone announced a second round of letters, dated August 11, to eight airlines: Alaska Airlines, American Airlines, Delta Air Lines, Frontier Airlines, Hawaiian Airlines, JetBlue Airways, Southwest Airlines, and United Airlines, with answers requested by August 25, 2026. The letters ask what information each carrier collects, how it is obtained, whether it plays any role in setting ticket prices, whether the carrier purchases or licenses consumer information from data brokers or other third parties, whether travelers can prevent their information from being used to set prices, and for studies, testing results, and internal projections on the revenue and sales effects of using consumer information. The letters do not accuse any carrier of unlawful conduct.
Pallone wrote that "I am very concerned about companies potentially using Americans' personal data to determine what prices they see and pay, and I am continuing an inquiry into just how widespread this practice is," and stated that "the airline industry specifically has faced several public allegations of surveillance pricing. One study found that an airline boosted its own revenue by as much as six percent by leveraging AI pricing based on consumer information, an increase that comes at the expense of consumers." The study is not identified in the press release (Source: democrats-energycommerce.house.gov).
At a press conference the same day, Pallone said the practice is "contributing to the larger affordability crisis," said the problem is worse in the airline industry than in groceries or any other industry, and said that although some of the 25 companies had responded, many define the practice differently, making it too early to identify a pattern that legislation should address (Source: nj.com).
State legislation
Two state statutes address the practice directly. The New York Algorithmic Pricing Disclosure Act (S 3008), signed July 8, 2025 with disclosure enforcement from November 10, 2025, requires businesses using algorithmic pricing to disclose the practice, backed by a per-violation penalty; a First Amendment challenge by the National Retail Federation is pending. The Maryland Protection from Predatory Pricing Act (HB 895), signed in late April 2026 and effective October 1, 2026, restricts surveillance pricing in grocery stores; advocates have identified loyalty-program and promotional-offer carveouts and the absence of a private right of action as limits on its reach.
New York Attorney General Letitia James has advocated moving from disclosure to prohibition through a two-bill package: the One Fair Price Act, which would ban surveillance pricing outright, and the Protecting Consumers and Jobs from Discriminatory Pricing Act, which would ban electronic shelf labels and prohibit surveillance pricing in grocery stores. As of May 2026, comparable bills were active in Colorado, California, Massachusetts, Illinois, and New Jersey.
Related industry episodes
Delta Air Lines announced and then withdrew plans for AI ticket personalization in August 2025 under Department of Transportation and congressional pressure. Following a Consumer Reports investigation, Instacart said it would stop using technology allowing grocery stores to charge different shoppers different prices for the same groceries, while stating it had never engaged in the practice.
Open questions
- Whether the FTC completes or formally closes the 6(b) study under current leadership has not been announced.
- The study Pallone cites for a six percent airline revenue increase is not named in the committee's public materials.
- Whether the pending National Retail Federation First Amendment challenge to New York's disclosure mandate constrains the state statutes that go further and prohibit the practice is unresolved.
Relationships
- related: Algorithmic Pricing and Antitrust — adjacent doctrine addressing pooled competitor data rather than individual consumer data
- depends-on: Three Privacy Problems AI Creates — individualized pricing depends on consumer profiling
- instance-of: AI Economic Primitives — pricing as an AI-mediated economic function
- regulated-by: Federal Trade Commission (FTC) — Section 6(b) market study and Section 5 authority
- related: New York Algorithmic Pricing Disclosure Act (NY S 3008) — state disclosure mandate
- related: Maryland Protection from Predatory Pricing Act — state prohibition in the grocery sector
- related: AI and Surveillance — shared data-collection substrate
Sources
- (Source: democrats-energycommerce.house.gov) — House Energy and Commerce Democrats, August 12, 2026: airline letters, FTC definition, quoted statements
- (Source: democrats-energycommerce.house.gov) — House Energy and Commerce Democrats, May 2026: initial 25-company inquiry
- (Source: ftc.gov) — FTC, January 2025: initial 6(b) staff findings
- (Source: ftc.gov) — FTC, "Issue Spotlight: The Rise of Surveillance Pricing"
- (Source: mccarter.com) — practitioner summary of the 6(b) tool and data-source taxonomy
- (Source: nj.com) — NJ.com, August 2026: Pallone press-conference statements