BizTech Law Blog

On August 19, 2026, the Federal Trade Commission voted 2-0 to release a proposed Enforcement Policy Statement Regarding Personalized Pricing and to open it for a 30-day public comment period once it is published in the Federal Register. For any business that sets prices online, or that is considering using data-driven or algorithmic pricing tools, this is a development worth watching closely.

What Is “Personalized Pricing”?

The FTC defines personalized pricing as the use of a consumer’s personal data to set prices based on an estimate of how much that specific individual is willing to pay, or whether that consumer is likely to comparison shop. It is sometimes called “surveillance pricing,” and it can draw on data points such as browsing history, location, shopping habits, purchase history, and household characteristics.

The Commission’s core concern is one of consumer expectations. As FTC Chairman Andrew Ferguson put it, “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 distinguishes this from ordinary price variation that consumers already expect, such as changes driven by supply and demand, regional taxes and regulations, or the individualized pricing inherent in products like insurance and credit.

The Legal Theory: Section 5 and Disclosure

Importantly, the FTC concedes that Congress has not given it authority to ban personalized pricing outright. Instead, the agency signals it will enforce aggressively under Section 5 of the FTC Act, which prohibits unfair or deceptive acts or practices.

The statement’s central message focuses on disclosure. Where consumers reasonably expect that a price will not vary based on their personal data, a business that engages in personalized pricing should clearly and conspicuously disclose:

• that the price is personalized;
• the basis for that personalization; and
• the types of data on which the personalization relies.

The failure to make these disclosures is likely to constitute an unfair or deceptive practice under Section 5. The FTC also warns that the undisclosed collection or use of personal data for personalized pricing—or basing prices on data without verifying the consumer consented to its collection—may independently raise Section 5 privacy concerns. The statement points to existing regimes, including the Fair Credit Reporting Act’s adverse-action notice requirements, the Restore Online Shoppers’ Confidence Act (ROSCA), and the Rule Against Unfair or Deceptive Fees, as consistent with its approach.

Examples

The policy statement offers several non-exhaustive examples of practices that would raise concerns, including:

• A food delivery company quoting higher prices to consumers it believes are less able to leave home to shop;
• A grocery chain charging more for milk based on data showing several children live in the household;
• A hotel charging more based on data suggesting a consumer is traveling for a funeral or other “can’t-miss” business;
• A rideshare company charging more because a user has not installed a competitor’s app; and
• A retailer raising the price of a home-security system based on court filings showing the customer was recently the victim of a crime.

Practical Implications

Personalized and algorithmic pricing has drawn scrutiny from both federal and state officials, including a broad investigation launched by the California Attorney General. Notably, the FTC declined to take a position on whether some personalized pricing practices could be unfair even when fully disclosed, leaving the door open to broader enforcement in the future.

Businesses that use, or are evaluating, data-driven or AI-assisted pricing, including tailored discounts, loyalty-program offers, and dynamic pricing engines, should consider a few practical steps now:

• Inventory where and how you use personal data to influence prices, discounts, or offers.
• Review your pricing disclosures and privacy notices for clarity on whether and how prices are personalized.
• Confirm you have appropriate consent for the data collection underlying any pricing decisions.
• Coordinate legal, marketing, and IT teams before deploying new pricing algorithms or third-party pricing tools.

How Foster Swift Can Help

Foster Swift’s Business & Tax and Cybersecurity and Data Privacy teams regularly counsel clients on FTC compliance, data privacy, and the responsible deployment of AI and algorithmic tools. If you would like to assess your pricing and data practices, evaluate the proposed policy statement’s impact on your operations, or prepare a public comment, please contact your Foster Swift attorney.