The Vote
On August 19, 2026, the Federal Trade Commission voted 2-0 to open public comment on a proposed Enforcement Policy Statement Regarding Personalized Pricing — the practice of using an individual consumer's data to set a price based on what a business estimates that specific person will pay. Comments close September 18, 2026. Chairman Andrew Ferguson framed the theory plainly: "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."
That single sentence carries the whole policy. The FTC is not proposing to ban personalized pricing. It is proposing to treat undisclosed personalization as a potential unfair or deceptive practice under Section 5 of the FTC Act — the same 111-year-old statute the agency has used against everything from fake reviews to dark patterns, applied here without any new rule or statute.
What the Statement Actually Requires
The draft statement says a business risks Section 5 liability if it individualizes prices from consumer data without clearly and conspicuously disclosing three things: the fact that the price is personalized, the basis for that personalization, and the categories of data used to set it. The FTC has been explicit that it lacks authority to prohibit personalized pricing outright — this is an enforcement posture applied to existing law, not a new prohibition.
The Case for Going Further
Consumer advocates make a real argument here, and it deserves a fair hearing before dismissing it. A months-long investigation by Consumer Reports and Groundwork Collaborative found that 74% of grocery items on Instacart carried different prices for different shoppers in tests across Safeway and Target stores, with the same item priced up to 23% apart — a gap the groups estimated could cost a family of four more than $1,200 a year. Instacart ended the practice, run through a vendor called Eversight, after the findings became public. Consumer Reports welcomed the FTC's move but argued it doesn't go far enough: "it should not be consumers' responsibility to read detailed disclosures on each item while shopping online to avoid being hit with a higher price." Writing in The American Prospect, David Dayen made a sharper version of the same point, noting the FTC's own examples — charging homebound customers more, or charging families with more children more for milk — "certainly sound unfair or deceptive" on their face, yet the statement declines to say personalized pricing is unlawful even when fully disclosed. Groundwork Collaborative's Lindsay Owens put it bluntly: Ferguson "makes it clear that he'll let companies play semantics as long as they disclose what they're doing."
Why Disclosure Is Still the Right Instrument
That critique proves too much. Price personalization is not inherently exploitative — it is also the mechanism behind senior discounts, student pricing, first-time-buyer promotions, loyalty pricing and geographic cost-of-living adjustments, all of which use personal characteristics or data to charge some customers less. A blanket ban aimed at Instacart-style manipulation would sweep in pricing structures that make goods more affordable for price-sensitive consumers. Section 5's unfairness and deception tests already ask whether a practice causes substantial, unavoidable injury or misleads a reasonable consumer — which is precisely the right filter for the line between deceptive manipulation and ordinary differentiated pricing. Using an existing statute through a policy statement, rather than a new rulemaking, also means the FTC can act now, during a 30-day comment window, instead of the multi-year process a Magnuson-Moss rulemaking would require. That is proportionate regulation: it targets the harm — concealment — rather than the underlying commercial practice.
A Patchwork the FTC Didn't Create
The federal statement arrives after states already diverged. New York's Algorithmic Pricing Disclosure Act (General Business Law § 349-A) took effect November 10, 2025, requiring a conspicuous notice — "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA" — with penalties up to $1,000 per violation. That is essentially the model the FTC is now proposing nationally. But New York has since moved past its own disclosure law: its legislature passed the One Fair Price Act, which would prohibit using personal data to generate individualized prices outright rather than merely requiring disclosure. New Jersey and California regulators are examining the practice through their own consumer-protection and privacy statutes. A national floor set through Section 5 enforcement — even a disclosure-only floor — gives businesses one clear federal standard to build compliance around instead of fifty divergent ones, which is a genuine value regardless of where one lands on the disclosure-versus-ban debate.
What to Watch
The FTC cannot fine anyone under a policy statement alone; it still has to bring and win individual Section 5 cases, and courts will decide case by case whether specific personalization practices meet the unfairness or deception bar. The real test comes after September 18, when the FTC finalizes the statement and picks its first enforcement target. Businesses using dynamic or individualized pricing should treat the comment period as a compliance deadline, not just a policy debate — auditing what data drives their pricing and disclosing it now costs far less than defending a Section 5 complaint later.