Different Shoppers, Different Prices

At a Glance

• On August 19, 2026, the Federal Trade Commission (FTC) proposed a new rule that would require companies that engage in personalized pricing to disclose that practice to consumers.
• At present, the proposed rule does not articulate the boundary between legitimate loyalty discounts and exploitative personalization, but the distinction could become central to any eventual enforcement action or rulemaking.

On August 19, 2026, the Federal Trade Commission (FTC) proposed a sweeping new policy that could reshape how businesses price goods and services online. The proposed rule would require companies that engage in personalized pricing to “clearly and conspicuously disclose” the practice to consumers and share the types of data used to set individualized prices. FTC Chairman Andrew Ferguson framed the proposal in consumer-trust terms: “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.”

Importantly, the proposal, rooted in Section 5 of the FTC Act (15 U.S.C. § 45), does not ban personalized pricing outright. Instead, the commission has concluded that failing to disclose the practice and its underlying data inputs may constitute an unfair or deceptive act. A 30-day public comment period is now open.

What the FTC Proposed

The FTC’s proposal establishes a disclosure obligation that requires businesses that charge different prices to different consumers based on personal data to (1) clearly disclose that fact to consumers before a purchase, and (2) identify the categories of data used in pricing decisions. The commission has acknowledged that it lacks the statutory authority to ban the practice entirely under Section 5, but it has asserted that nondisclosure of material pricing practices is deceptive within the meaning of the statute. This approach mirrors prior FTC actions in the data privacy space, where disclosure failures have served as the predicate for enforcement.

How Technology Changes Prices Online vs in Physical Stores

A physical shelf displays the same price to every consumer who walks past. Online retail operates fundamentally differently. Algorithms can adjust prices, product rankings, promotions, and offers in real time based on individual consumer profiles. This means two consumers visiting the same retailer’s website at the same moment may see different prices for identical products. The FTC’s January 2025 preliminary report on surveillance pricing confirmed that grocers, apparel companies, and other retailers are actively using third-party data intermediaries to individualize online prices. The report was based on the examination of documents obtained from intermediary firms that provide data analytics, pricing optimization, and consulting services to retailers. Staff found that these intermediaries worked with at least 250 clients selling goods and services ranging from grocery to apparel, and that the tools they offer have the capability to generate “higher priced products based on consumers' search and purchase activity.” The report found that companies rely on consumer location, browsing histories, time spent on product pages, and items left in shopping carts to calibrate pricing in ways that would be impossible in a brick-and-mortar environment.

What Data Is Tracked

The scope of consumer data feeding pricing algorithms is broad. According to the FTC’s findings, companies track browsing history, search queries, click patterns, cart abandonment behavior, purchase history, account and loyalty program status, geographic location, device information, time of visit, and repeat visit frequency. Beyond directly observed behavior, companies also use this data to infer characteristics such as household income, urgency of need, price sensitivity, and overall willingness to pay. These inferred attributes often drive the most significant pricing differentials.

The Loyalty Program Gray Area

One of the most significant open questions involves the boundary between legitimate loyalty discounts and exploitative personalization. In a traditional loyalty program, the consumer opts in, sees a baseline price, and receives a clearly stated benefit in exchange for participation. The consumer understands the terms, can compare the member price to the standard price, and makes an informed decision about whether to join.

Personalized pricing operates differently. Algorithms may identify consumers who appear less price-sensitive and adjust their prices upward, without any transparent baseline or opt-in mechanism. The consumer never learns that someone else saw a lower cost for the same product at the same time.

Consider the parent searching for a children’s thermometer at 3 a.m. Pricing algorithms can infer urgency from the time of purchase and browsing behavior, potentially resulting in a higher price precisely when the consumer is least able to comparison-shop. The consumer has no way to know that the same thermometer was available for a lower price six hours earlier, or that another shopper in a different behavioral profile would see a reduced price at that same moment.

The FTC’s proposal does not draw a bright line between these scenarios. It does not specify how much personalization transforms a loyalty benefit into a deceptive practice, nor does it define when inferred urgency crosses from legitimate market responsiveness into exploitation. We anticipate these interpretive questions will be central to the 30-day comment period and any eventual enforcement action or rulemaking.

Industries in the Government’s Crosshairs

The FTC’s investigative work and public statements seem to have focused on three sectors: grocery, apparel, and broader e-commerce. The January 2025 report specifically examined companies in these industries that used third-party surveillance pricing services. Retailers in these sectors should assume they face heightened scrutiny, particularly those with significant online sales channels and sophisticated data collection infrastructure. The FTC's proposed policy statement underscores the point by offering hypothetical examples of scenarios that would raise Section 5 concerns. These include:

• 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
• A grocery chain charging a delivery customer a higher price for milk based on data showing that several children live in the customer's household
• A hotel charging a higher price based on data indicating the consumer is traveling for a funeral or other "can't-miss" personal event
• A rideshare company charging a user more because data reveals they have not installed any competitor apps on their phone
• A rideshare company charging more for transport to a medical facility based on data suggesting the user has a life-threatening medical emergency
• A retailer charging more for a home-security camera system based on court filings indicating the customer was recently a crime victim
• A retailer charging more on its website based on data revealing the consumer is currently inside one of the retailer's physical stores or parking lots while browsing online

The FTC noted these are hypothetical illustrations "presented for discussion purposes only," but they provide an indication of the type of conduct most likely to attract enforcement attention.

Industry trade groups, including the National Retail Federation, the Food Marketing Institute, and the Retail Industry Leaders Association, have pushed back on the proposal, arguing that retailers do not use personal data to increase prices and that legitimate loyalty programs would be chilled by overly broad disclosure requirements.

State Legislative Landscape

The FTC’s action arrives against a backdrop of significant state-level activity. Maryland and New Jersey have enacted legislation banning personalized pricing in the grocery sector, while Connecticut’s law applies more broadly to retailers and third-party delivery services. New York’s Algorithmic Pricing Disclosure Law is now in effect, and California’s AB 2564, which would impose sweeping restrictions on “surveillance pricing,” is still pending adoption. Companies operating across multiple states face a patchwork compliance challenge: even if the FTC’s proposal remains disclosure-based at the federal level, state laws may prohibit the practice outright in certain sectors or jurisdictions. Multistate retailers should evaluate their pricing practices against both the proposed federal framework and the rapidly evolving state landscape.

What Businesses Should Do Now

Audit Current Pricing Practices

Identify whether algorithms adjust prices based on individual consumer data (as distinct from market-wide supply and demand factors).

Map Data Inputs

Document the categories of consumer data flowing into pricing decisions, including data obtained from third-party intermediaries.

Evaluate Loyalty Programs

Assess whether loyalty or membership programs use data in ways that go beyond providing stated discounts to enrolled consumers.

Consider Submitting Comments

The 30-day comment period provides an opportunity to shape the final rule, particularly on the loyalty program question and the scope of required disclosures.

Monitor State Developments

Track pending legislation in California, New York, and other states where personalized pricing restrictions are advancing.

Engage Outside Counsel

Companies in the grocery, apparel, and e-commerce sectors should consult with counsel experienced in FTC enforcement and consumer protection to assess exposure and develop a compliance roadmap.