In brief
The Federal Trade Commission (FTC or Commission) released for public comment a proposed enforcement policy statement signaling that it will enforce Section 5 of the FTC Act against deceptive or unfair practices associated with personalized pricing, meaning consumer-specific prices informed by personal data or inferences such as willingness to pay or likelihood of comparison shopping. The proposal does not declare personalized pricing unlawful as a category. Instead, the FTC’s core message is disclosure focused. Where consumers reasonably expect that prices will not vary based on their personal data, businesses engaged in personalized pricing “should clearly and conspicuously disclose not just that the price is personalized, but also the basis for that personalization and the types of data on which the personalization is based.” The FTC pronounced that “[t]he failure to make these disclosures is likely to constitute an unfair or deceptive act or practice in violation of Section 5. The Commission intends to deploy enforcement resources in a manner consistent with this conclusion.”
Comments are due September 18, 2026, at 11:59 p.m. EDT.
Key takeaways
- No categorical federal ban. The FTC acknowledged that it lacks authority to prohibit personalized pricing in every circumstance. Any enforcement case would still have to rest on an existing statute or rule.
- Market context matters. The FTC’s theory is strongest where customary practice leads consumers reasonably to expect that similarly situated shoppers will see the same price at the same time and place. The proposal distinguishes those settings from insurance, credit, rideshare surge pricing, and other markets where individualized pricing is established or inherent.
- The statement describes an example of adequate disclosure. A clear and conspicuous disclosure that a price reflects the consumer’s estimated willingness to pay, derived from that consumer’s prior purchases from the same retailer through the same login account, would — “if accurate and complete” — likely suffice.
- Pricing governance and privacy governance converge. The proposal treats data provenance, purpose disclosure, and consent as independent compliance questions, including when a business obtains data from vendors or other third parties.
- Unfairness remains fact intensive. The Commission suggests that a concealed higher price may cause unavoidable monetary injury, but expressly reserves judgment on whether a fully disclosed personalized pricing practice could nevertheless be unfair.
- The proposal is not binding law. Although the proposed statement does not create new legal obligations, it serves as an enforcement warning that the FTC is prepared to use its existing enforcement authority under Section 5 and foreshadows potential rulemaking.
In more detail
A disclosure framework tied to consumer expectations
The proposal centers the deception analysis on the message conveyed by the pricing interface and the surrounding market practice. A business could face scrutiny if it states or implies that a price is generally applicable when the price is actually calculated for a particular consumer. The same concern may arise from a lack of disclosure if consumers would reasonably understand the displayed price to be common rather than individualized. However, the FTC would still need to establish that the challenged representation or omission was likely to affect a reasonable consumer’s purchasing conduct.
The proposed statement also focuses on the accuracy of a business’s explanation. Describing an offer as a loyalty benefit could be misleading, for example, if the algorithm instead raises the price because external data indicates greater disposable income or lower likelihood of switching to a competitor. Businesses should evaluate not only whether a disclosure appears, but whether it accurately describes the operative pricing logic and data inputs.
The statement also describes what an adequate disclosure could look like. Telling a consumer only that he is being shown a “specially selected” price would likely be misleading because it omits material information. By contrast, a clear and conspicuous disclosure that a personalized price is based on the consumer’s estimated willingness to pay, derived from data about that consumer’s previous purchases from the same retailer through the same login account, would, if accurate and complete, likely be enough to disclose that the price is personalized.
Data collection, use, and vendor-derived information
The FTC separately cautions that the data practices supporting a pricing model may be deceptive or unfair. A stated purpose for collecting information should be compared against its actual use in pricing. The proposal also signals that a business may need a reasonable basis for concluding that consumers consented to the relevant collection and use, rather than relying on a data supplier’s contractual assurances. This is especially important where a pricing engine combines first-party purchase history with location, browsing, device, or other third-party information.
Other FTC-administered requirements may apply
The Commission notes that the same conduct may implicate other laws or regulations it enforces. For example, the Restore Online Shoppers’ Confidence Act prohibits charging consumers for subscriptions without their express informed consent as well as failing to clearly and conspicuously disclose all material terms of the transaction before consumers provide their payment information, and the Rule on Unfair or Deceptive Fees prohibits misleading consumers about fees in the live-event ticketing and short-term lodging industries. Depending on the product, data source, and pricing decision, businesses should also evaluate sector-specific federal and state requirements rather than treating the proposed statement as a complete compliance framework.
Examples the FTC says could raise concerns
The proposal uses nonexclusive illustrations to show the kinds of inferences that may attract scrutiny when they are used to increase an undisclosed individualized price. They include raising a price because data suggests that a consumer:
- Is unable or unlikely to leave home to obtain food;
- Is a delivery customer purchasing milk in a household where children live;
- Is traveling for a funeral or another urgent personal obligation;
- Does not have competing rideshare applications installed;
- Is seeking rideshare transportation during a medical emergency;
- Was a recent crime victim, according to court records, and is buying a home-security camera system; or
- Is browsing a retailer’s website while physically present in the retailer’s store or parking lot.
These scenarios are illustrations, not adjudicated violations. The legal outcome would depend on the representation or omission, the consumer’s reasonable understanding, materiality, the nature and avoidability of any injury, countervailing benefits, and the evidentiary record.
Recommendations
Companies that use or are considering whether to implement dynamic pricing should consider taking the following steps and consult counsel in the future regarding any applicable FTC rulemaking.
- Map pricing decisions end to end. Identify every channel in which a consumer-specific price or discount is set, ranked, or recommended. Document the model, decision rules, data inputs, inferences, vendors, affected products, and points at which a consumer sees or accepts the price.
- Assess the consumer’s likely takeaway. Review the full interface, marketing language, loyalty messaging, and customary market practice. Determine whether the presentation communicates a common price, a discount, or a consumer-specific price, and whether that message is accurate.
- Design disclosures around the actual pricing logic. If personalization is used, evaluate a proximate, unavoidable, and understandable disclosure that explains the fact of personalization, the principal basis for it, and the categories of data used. Avoid vague labels that could imply a benefit without explaining that personalization may increase the price.
- Test whether “dynamic pricing” is personalized pricing. Many businesses use dynamic pricing models. But if an input to the model consists of data about the individual consumer rather than a condition of the market, disclosure may be necessary.
Ethan Primeaux, Associate, has contributed to this legal update.