FTC Proposes Enforcement Policy Statement on Personalized Pricing: What Businesses Need to Know

The Federal Trade Commission (FTC) announced on August 19, 2026, that it is seeking public comment on a proposed enforcement policy statement regarding "personalized pricing," which is defined as the practice of using personal data to set prices according to the amount a company believes an individual consumer is willing to spend. The FTC voted 2-0 to issue the proposed statement.

FTC Chairman Andrew Ferguson stated: "When consumers see a listed price, they expect it to be the same price that everyone else sees, not the retailer's estimate of how much they are willing to pay based on their personal data. The FTC does not have the legal authority to ban personalized pricing in all circumstances, but businesses that fail to tell consumers how their personal data is being used to set a price may be in violation of the FTC Act and other laws we enforce."

This Holland & Knight alert summarizes the key provisions of the proposed policy statement, analyzes the FTC's legal theories and provides actionable guidance for businesses that use or may consider using consumer data in pricing decisions. For additional information on surveillance pricing enforcement, see Holland & Knight's previous alerts, "Surveillance Pricing, AI Pricing Tools and the Push for Price Transparency" (April 27, 2026) and "Surveillance Pricing and Dynamic Pricing: What General Counsels Need to Know" (August 5, 2026), which provide detail on state legislative developments, the Robinson-Patman Act's reemergence and the FTC's Advance Notice of Proposed Rulemaking (ANPRM).

What General Counsels Should Do Now

Companies using consumer data to set individualized prices – or those who may do so in the future – should take the following steps:

• Audit Pricing Algorithms and Data Practices. Determine whether any pricing models use personal data to set individualized prices. Include third-party vendors in this assessment.
• Implement Clear Disclosures. If personalized pricing is used, disclosures must explain 1) that the price is personalized, 2) the basis for personalization and 3) the data types used. Vague language such as "specially selected" is insufficient.
• Review Consent Mechanisms and Privacy Policies. Verify consumer consent specifically covers pricing use. Update privacy policies and terms of service to accurately describe data use for pricing purposes.
• Assess Vulnerability-Based Pricing Risks. Algorithms using data indicating consumer vulnerability (health conditions, family circumstances, lack of alternatives) present the highest enforcement risk.
• Consider Submitting Comments. The public has 30 days from the date of the Federal Register publication to submit comments. Comments may be submitted online (Docket Number: FTC-2026-1057). Companies that may be affected by this policy statement should consider engaging with the FTC during the comment period to advocate for clear, workable standards.
• Monitor State Developments. New Jersey, Maryland and Connecticut have addressed personalized pricing, with Maryland and Connecticut measures taking effect in October 2026 and New York's One Fair Price Act awaiting the governor's signature. Compliance with overlapping federal and state obligations is essential.

Background

The proposed policy statement is the latest in a series of actions by the FTC under President Donald Trump's leadership, targeting businesses that mislead consumers with hidden fees and surprise charges. Though personalized pricing – where different consumers pay different prices for the same product based on their individual characteristics – has existed in various forms (e.g., insurance, financial services), the FTC notes that advances in data analytics and artificial intelligence (AI) have dramatically expanded the potential for such practices across consumer markets.

The FTC acknowledges that the U.S. Congress has not granted it authority to prohibit personalized pricing outright. However, the FTC signals its intent to enforce aggressively against personalized pricing practices that are deceptive or unfair under Section 5 of the FTC Act or that violate any other law the FTC enforces.

Notably, the FTC observes that while consumers generally expect prices to vary based on supply and demand, they do not expect prices to vary based on their personal data in markets where pricing has traditionally been uniform. Economic research cited in the statement suggests that personalized pricing is likely to increase business profits, but the benefits to some consumers are accompanied by losses to others, and more sophisticated practices are less likely to benefit consumers overall.

Broader Regulatory Context

This policy statement does not exist in isolation. Federal and state regulators have been converging on surveillance pricing and algorithmic pricing practices from multiple angles simultaneously. For example, in 2024, the FTC launched a Section 6(b) study examining how companies and intermediaries use consumer data to implement surveillance pricing. That study, published in January 2025, confirmed surveillance pricing is widespread.

In April 2026, the FTC issued an ANPRM covering total price disclosure, fee transparency, personalized pricing disclosure and unauthorized billing protections. In congressional testimony that same month, FTC leadership confirmed that staff work on surveillance pricing continues and the agency is assessing whether additional disclosures may be required. The latest proposed policy statement marks the culmination of that sustained focus – translating the FTC's information-gathering posture into a concrete enforcement framework.

Meanwhile, state attorneys general (AGs) have moved faster than federal regulators. As detailed in prior alerts, New Jersey's Fair Price Protection Act (signed on July 23, 2026) bans personalized algorithmic pricing for grocery retailers and delivery platforms, and Maryland bans surveillance pricing for food retailers (effective October 1, 2026). Connecticut requires disclosures for certain personalized algorithmic pricing practices (effective October 1, 2026). In addition, New York's One Fair Price Act passed the state legislature on June 10, 2026, and awaits the governor's signature. California AG Rob Bonta has opened investigations under the California Consumer Privacy Act's purpose limitation provisions, treating pricing-related data use as potentially exceeding disclosed purposes. Companies operating in multiple jurisdictions must now navigate both the FTC's disclosure-based enforcement approach and these emerging state-law prohibitions.

In addition, congressional scrutiny is intensifying. The U.S. House of Representatives Committee on Oversight and Government Reform launched a formal investigation into AI-driven pricing in March 2026, and a coalition of 16 state AGs – led by New York and Tennessee – urged the FTC to issue a separate rule targeting personalized or surveillance pricing. The bipartisan attention to this issue significantly increases the risk that enforcement actions or rulemaking may follow quickly.

Key Provisions of the Policy Statement

Disclosure Requirements

The policy statement's core requirement is that where consumers reasonably expect prices will not vary based on personal data, businesses engaging in personalized pricing must provide clear and conspicuous disclosures of the following:

1. the fact that the price is personalized
2. the basis for that personalization
3. the types of data on which the personalization is based

Failure to make these disclosures is, in the FTC's view, "likely to constitute an unfair or deceptive act or practice in violation of Section 5."

Adequacy of Disclosures

The FTC provides guidance on what constitutes adequate versus inadequate disclosure:

• Telling a consumer that they have been shown only a "specially selected" price would likely be misleading because it omits important information about the nature and basis of personalization.
• A clear and conspicuous disclosure that a personalized price is based on a consumer's estimated willingness to pay derived from data about that consumer's previous purchases from the same retailer through the same login account – if accurate and complete – would likely be sufficient.

Data Practices and Consent

The policy statement addresses data collection and consent requirements:

• Businesses that collect, use or disclose consumers' personal data for personalized pricing without adequate disclosures or without obtaining consent may violate Section 5.
• Businesses that base personalized prices on personal data without sufficiently verifying that consumers consented to the collection of those data for that specific purpose may also violate Section 5.

The FTC's Legal Theory

Deception Under Section 5

The FTC applies its long-standing three-part test for deception. An act or practice is deceptive if it involves a representation, omission or practice that is 1) material, 2) likely to mislead a consumer acting reasonably under the circumstances and 3) to the consumer's detriment.

The FTC identifies several scenarios constituting deception, including:

• representing that a price is static or widely offered when it is in fact personalized
• failing to disclose that a price is personalized when a consumer reasonably believes it is static or widely offered
• misleading consumers as to the basis for personalization or the effect of that personalization on the price shown

Unfairness Under Section 5

An act or practice is unfair if it 1) causes substantial injury to consumers, 2) is not reasonably avoidable by consumers, and 3) is not outweighed by countervailing benefits to consumers or competition. The FTC's reasoning includes the following:

• Substantial Injury. The higher price paid due to personalized pricing may constitute substantial injury.
• Not Reasonably Avoidable. Consumers may not be able to avoid the higher price if the fact or nature of personalization has been concealed from them.
• Countervailing Benefits. Economic research suggests more sophisticated, personalized pricing practices are less likely to benefit consumers.

Other Applicable Laws

The policy statement notes that personalized pricing practices may also implicate:

• Restore Online Shoppers' Confidence Act (ROSCA)
• Rule Against Unfair or Deceptive Fees (16 C.F.R. Part 464)
• Fair Credit Reporting Act (cited as an analogy for disclosure requirements in industries with established personalized pricing)

Illustrative Examples of Problematic Practices

The policy statement identifies specific examples of personalized pricing practices likely to raise enforcement concerns:

1. a food delivery company quoting a higher price to consumers based on data suggesting they are less likely or unable to leave their homes to purchase food
2. a grocery chain charging a delivery customer a higher price for milk based on data showing several children live in the customer's household
3. a hotel charging a higher price based on data indicating the consumer is traveling for a funeral or other can't-miss personal business
4. a ride-share company charging a user more based on data revealing the user has not installed any competitor apps
5. a ride-share company charging more for transport to a medical facility based on data suggesting a life-threatening medical emergency
6. a retailer charging more for a home-security camera system based on court filings indicating the customer has recently been a crime victim
7. a retailer charging more for a product on its website based on data revealing the consumer is inside one of the retailer's physical locations or parking lots

These examples share a common theme: the use of data indicating consumer vulnerability or reduced alternatives to extract higher prices without disclosure.

The Bottom Line

AI is now a risk multiplier when used in pricing, merchandising, bundling or fee presentation. The FTC has emphasized that machine learning and automated experimentation enable granular consumer segmentation, rapid A/B price testing and optimization processes that are largely invisible to consumers. Companies that deploy AI pricing tools should treat those tools as heightening – not reducing – their disclosure and governance obligations under this policy statement.

Although the policy statement does not confer any rights and does not bind the FTC or the public, it provides clear signals about the FTC's enforcement priorities.

For more information or questions on a specific matter, please contact the authors.

Information contained in this alert is for the general education and knowledge of our readers. It is not designed to be, and should not be used as, the sole source of information when analyzing and resolving a legal problem, and it should not be substituted for legal advice, which relies on a specific factual analysis. Moreover, the laws of each jurisdiction are different and are constantly changing. This information is not intended to create, and receipt of it does not constitute, an attorney-client relationship. If you have specific questions regarding a particular fact situation, we urge you to consult the authors of this publication, your Holland & Knight representative or other competent legal counsel.