Personalized Pricing Enters the FTC Section 5 Spotlight: What Retailers, Platforms, and Consumer-Facing Businesses Need to Know

By: Daniel J. Gershman

The FTC’s proposed policy statement warns that using personal data to set individualized prices without clear disclosure may create liability under Section 5. It is not a federal ban on personalized pricing, but the warning is clear: if customers do not know their price is personalized, the FTC may view the practice as deceptive or unfair. 

If your company uses personal data, such as loyalty data, browsing history, location, or purchasing behavior, to adjust prices for individual consumers, pay close attention. On August 19, 2026, the Federal Trade Commission (FTC) voted 2-0 to seek public comment on a proposed enforcement policy statement about personalized pricing, sometimes called “surveillance pricing.” The FTC defines personalized pricing as using personal data to set a price based on what a company thinks an individual consumer will pay. 

This is the FTC’s most significant action on the topic since its 2024 surveillance pricing study. It comes as state laws continue to take shape, including New York’s Algorithmic Pricing Disclosure Act, which is already in effect. For any consumer-facing business that personalizes offers or prices, including retailers, ecommerce platforms, and subscription services, the practical question is simple: are your disclosure practices adequate? 

What the FTC Proposed 

The proposed policy statement is not a ban on personalized pricing or a trade regulation rule, and it does not itself authorize monetary penalties. Instead, it puts businesses on notice of how the FTC interprets Section 5 in this context. As FTC Chairman Andrew Ferguson explained, consumers expect a listed price to be the same price everyone else sees, not a retailer’s estimate of what they are willing to pay based on personal data. The FTC acknowledged it cannot prohibit personalized pricing in every circumstance but emphasized that failing to disclose that personal data is used to set a price may violate the FTC Act. 

The proposed statement identifies three types of conduct that may violate Section 5: 

1. Deceptive representations. Saying or implying that a price is fixed or widely available when it is personalized or presenting a higher personalized price as a “loyalty discount” or similar benefit. 
2. Failure to disclose. Failing to disclose personalization when consumers reasonably believe the price is fixed or widely available. The FTC expects businesses to explain that the price is personalized, why it was personalized, and what data informed it. 
3. Unfair data practices. Collecting, using, or sharing consumers’ personal data to set personalized prices without adequate disclosure or consent. This also includes using personal data for pricing without verifying that consumers consented to that specific use. 

The FTC identified several pricing practices it views as problematic: a food delivery service charging more when data suggests a consumer is less able to leave home; a grocery chain charging more for milk when data indicates the household includes children; a hotel raising rates when data suggests a guest is traveling for a funeral; a rideshare service charging more when its data shows the user does not have competing apps; and a retailer raising prices when it detects that a consumer is browsing online while inside one of its stores. 

What This Is and What It Is Not 

Businesses should understand the legal significance of this document. The proposed policy statement: 

• Is not a final rule. It has no force as a trade regulation rule and does not itself authorize monetary relief. 
• Does not bind the FTC or the public. In any enforcement action, the FTC must prove a violation of an existing statutory or regulatory requirement. 
• Does provide notice. It signals the FTC’s enforcement approach and provides a roadmap of what the Commission may consider inadequate disclosure. Treat it as advance warning. 
• Is open for comment. The public comment period lasts 30 days after publication in the Federal Register. Businesses and industry groups can submit input before the statement is finalized. 

The State-Law Backdrop: New York and Beyond 

This federal proposal arrives as state legislatures have already acted. New York’s Algorithmic Pricing Disclosure Act (General Business Law § 349-a), effective November 2025, requires businesses domiciled or doing business in the state that use personalized algorithmic pricing to give New York consumers a clear and conspicuous disclosure: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” 

The New York statute applies broadly to entities doing business in the state. It defines “personal data” as information that could reasonably be linked to a specific consumer or device and authorizes the Attorney General to seek injunctive relief and civil penalties of up to $1,000 per violation after an opportunity to cure. No proof of actual consumer injury is required. 

Separately, a New York surveillance pricing ban was awaiting the governor’s signature as of late August 2026. Maryland, New Jersey, and Connecticut have enacted related laws, and more than 50 surveillance pricing bills are pending in 26 states. 

For national businesses, the takeaway is clear: even if the FTC has not finalized its proposed statement, state law may already require disclosures, particularly for businesses that sell to New York consumers. 

Practical Steps for Compliance 

Businesses should consider these steps to prepare for the proposed FTC framework and existing state-law requirements: 

1. Audit your pricing inputs. Identify every instance in which personal data influences pricing, including browsing or purchasing history, location, demographics, device and app data, loyalty-program activity, and inferred traits such as willingness to pay. Do not assume seemingly innocuous transaction history is excluded. 
2. Evaluate disclosure practices. Determine whether consumers are clearly told when a price is personalized, why it was personalized, and what data was used. Under the FTC’s proposed framework, generic privacy-policy language is unlikely to suffice. Disclosures should be clear and conspicuous at or near the point of purchase. 
3. Assess New York compliance. If your business is domiciled in New York or sells to New York consumers using algorithmic pricing based on personal data, confirm that it provides the required statutory disclosure. The New York AG has encouraged consumers to report undisclosed algorithmic pricing. 
4. Review consent mechanisms. The FTC’s proposed statement flags using personal data for pricing without verifying that consumers consented to that use. Ensure that your data collection notices and consent flows cover pricing uses, not just marketing or analytics. 
5. Monitor state laws. With legislation pending in dozens of states, disclosure and consent obligations may expand. Implement a monitoring process and consider disclosure mechanisms that accommodate state-by-state differences. 
6. Consider submitting a comment. The 30-day comment period is an opportunity to shape the FTC’s final statement. Businesses and industry groups concerned about ambiguity, such as the undefined scope of “personal data” or what qualifies as adequate disclosure, should consider submitting comments. 

Key Takeaways 

• The FTC’s proposed policy statement signals that undisclosed personalized pricing, charging consumers different prices based on personal data without telling them, may be deceptive or unfair under Section 5 of the FTC Act. 
• This is not a ban on personalized pricing. It is a proposed disclosure standard: tell consumers when pricing is personalized, explain why, and identify the data used. 
• New York’s Algorithmic Pricing Disclosure Act is already in effect and requires businesses that use algorithmic pricing based on personal data to provide a specific disclosure when selling to New York consumers. 
• State-law momentum is accelerating. More than 50 bills are pending in 26 states, making systems for state-specific pricing disclosures increasingly important. 
• Businesses using loyalty data, browsing behavior, location, purchasing history, or AI-driven pricing algorithms should audit their inputs, review disclosure and consent practices, and prepare for increased federal and state scrutiny. 

How Can FRB Help? Falcon Rappaport & Berkman’s corporate, privacy, and advertising teams advise companies on algorithmic pricing compliance, FTC enforcement risk, consumer disclosures, and multistate regulatory strategy. We can help audit pricing inputs, design compliant disclosure frameworks, prepare an FTC comment, or assess exposure under New York’s disclosure law. Contact us today to discuss your needs. 

This post is for informational purposes only and does not constitute legal advice. The information contained herein should not be relied upon in making legal or business decisions without first consulting an attorney.