Lawmakers and regulators at both the state and federal levels are increasingly focusing on consumer protection considerations relating to algorithmic pricing. On September 25, the Federal Trade Commission (“FTC”) closed the comment period on a proposed enforcement policy statement on personalized pricing. The proposed statement is the FTC’s preliminary view on whether personalized pricing practices could be deceptive or unfair, and on when the agency would expect an affirmative disclosure when personalized pricing is used. The FTC’s proposed policy statement drew more than 4,500 comments from a variety of perspectives, such as small businesses, food, and technology. Many commenters raised concerns about the statement’s current broad scope, including whether the FTC would distinguish between use cases involving personal data to provide individualized price increases on the one hand and discounts or other savings or promotions that lower prices for consumers on the other. Commenters also urged the agency to preserve loyalty programs and other long-standing practices in which companies provide tailored pricing to certain customer segments.
On October 28, 2026, the FTC announced it is also conducting a market study of certain participants to understand whether industry utilizes personal data to set pricing and compensation. This follows the Commission’s earlier study on personalized pricing from 2024 and the FTC staff’s publication of initial findings from that study.
If it becomes final, the FTC’s policy statement would serve as a federal counterpart to New Jersey, New York, Connecticut, and Maryland, which have all enacted laws that address these practices and many more states that have proposed legislation. The legislative trend is also extending to the local level, with Seattle becoming the first city to prohibit certain algorithmic pricing practices. Generally, these laws target the use of personal data and algorithmic tools to set individualized prices. However, there is significant variation in the legal approaches:
- Sector-specific bans (New Jersey, Maryland, Seattle). New Jersey’s Fair Price Protection Act prohibits using “surveillance pricing” to determine or vary the sale price of groceries and other foodstuffs based on personal data. Maryland’s Protection from Predatory Pricing Act prohibits food retailers and third-party delivery providers from using “dynamic pricing” to set higher prices for covered grocery items. Seattle’s ordinance prohibits a delivery service provider, mixed-use grocery business, or a grocery business that has 20 or more retail locations globally from using “algorithmic-based price discrimination.”
- Disclosure (New York). New York’s law applies across sectors and requires businesses to clearly disclose when they are using personalized algorithmic pricing. The New York legislature also passed amendments that would shift away from a disclosure-based approach and instead prohibit “surveillance pricing.”
- Ban and Disclosure (Connecticut). Connecticut prohibits retail sellers and third-party delivery services from using algorithmic pricing for any purpose other than setting a discounted price, subject to exceptions. Where an exception applies, the business must disclose: “This price was increased using your personal data”.
Key Challenges
Broadly-drafted laws may sweep in and even prohibit common pricing strategies that benefit consumers, such as personalized coupons, loyalty rewards, and targeted discounts. Exceptions for discounts are not uniform across jurisdictions.
Accordingly, given the patchwork of state algorithmic pricing laws and the potential for federal enforcement if the FTC policy statement is finalized, businesses should determine whether they are a covered entity, what practices may be impacted by these laws, whether there are any statutory exceptions that would apply, and identify the marketing collateral and pricing flows that may require updates to comply with bans or disclosure requirements.
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