Personalized pricing means an online store uses an algorithm and data about a shopper to set or adjust the price that shopper sees. In the United States, a New York law now requires the sentence "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA" next to such prices, and the Federal Trade Commission (FTC) published interim findings on the practice on January 17, 2025. Canada has no comparable disclosure rule, but the Competition Bureau has described the practice and noted that false or misleading statements about data collection are illegal.
Key takeaways
- Dynamic pricing reacts to market conditions such as demand and stock; personalized pricing, also called surveillance pricing, tailors prices to the individual shopper.
- The FTC's January 2025 findings were interim and drew on documents from six intermediary companies, not on a full public report.
- New York's Algorithmic Pricing Disclosure Act requires a fixed disclosure sentence and allows civil penalties of up to USD 1,000 per violation.
- A federal judge rejected a First Amendment challenge to the law on October 8, 2025, and an appeal was reported as pending.
- Canada's Competition Bureau published a June 2025 discussion paper that makes no policy recommendations.
Dynamic pricing and personalized pricing are different things
Online prices have moved with demand for decades. Airlines, ride services, and hotels change prices by time, season, and inventory, and shoppers can usually see that the same item costs more on a busy day. Personalized pricing is a narrower idea: the price or the discount depends on who is looking. Canada's Competition Bureau draws the line in its June 10, 2025 discussion paper on algorithmic pricing, which defines dynamic pricing as algorithms that set or recommend prices based on market conditions, and personalized pricing as algorithms that tailor prices to individuals or groups using consumer data such as demographics, online behavior, and transaction history. The paper adds that the two are hard to tell apart in practice, because firms often feed an algorithm both kinds of data.
The distinction matters for law. A price that rises because a product is nearly sold out affects every visitor. A price that differs because of a shopper's location, device, or purchase history raises questions about privacy, fairness, and what a store must tell people.
What the FTC study found, and what it did not
In July 2024 the FTC sent orders under Section 6(b) of the FTC Act to eight companies that provide pricing tools, asking how they use personal data. On January 17, 2025, the agency released preliminary findings based on documents from six of them: Mastercard, Accenture, PROS, Bloomreach, Revionics, and McKinsey & Co. The study looks at intermediaries, which retailers hire to adjust and target prices algorithmically.
Staff reported that the data used for pricing can include location, demographics, browsing patterns, and shopping history, and that even mouse movements and items left in a cart can be tracked. The intermediaries worked with at least 250 clients, including grocery and apparel retailers. One example involved a cosmetics company targeting promotions by skin type and skin tone.
The limits are as important as the findings. The agency releases information from these studies only in aggregated or anonymized form, so the staff perspective contains hypothetical examples, not named cases of a specific shopper paying more. The Commission voted 3-2 to release the material, and Commissioners Andrew Ferguson and Melissa Holyoak issued a dissenting statement about releasing the research summaries. A report from the American Bar Association dated April 2026 still described the study as ongoing, and no final report turned up in the searches made for this article.
New York's disclosure law
New York General Business Law section 349-a covers "personalized algorithmic pricing," defined as dynamic pricing set by an algorithm that uses personal data tied to a specific consumer or device. A business that advertises or offers such a price to a New York consumer must show the disclosure "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA," clearly and conspicuously, with the price. The statute exempts insurers, certain financial institutions, and subscription prices that are lower than the existing subscription price.
Enforcement runs through the state attorney general. After a complaint or other reason to suspect a violation, the office must first send a cease-and-desist letter with a deadline to fix the problem. If violations continue, it may seek an injunction, and a court may impose a civil penalty of up to USD 1,000 per violation.
The National Retail Federation sued to block the law. On October 8, 2025, Judge Jed Rakoff of the Southern District of New York dismissed the challenge, holding that the sentence is a factual disclosure that does not violate the First Amendment under the Zauderer standard for commercial disclosures. Secondary reports say the federation appealed to the Second Circuit, and the current status of that appeal could not be confirmed from a primary source.
Where the rules stand in each country
The table is a simplified map of the sources reviewed in October 2026, not a full legal survey.
| Question | United States | Canada |
|---|---|---|
| Is there a federal rule that requires a notice about algorithmic prices? | None found; the FTC study is interim | None found; the Competition Bureau paper is a discussion paper |
| Is there a state or provincial rule? | New York section 349-a, litigated and reported on appeal | None found in the sources reviewed |
| What general rule applies to statements about data? | FTC Act ban on deceptive practices | Competition Act ban on false or misleading representations |
| What did officials publish? | Interim staff findings, January 17, 2025 | Discussion paper, June 10, 2025 |
On the Canadian side, the Competition Bureau paper says the representations most likely to raise concerns are those about whether data is collected, what is collected, why, whether it is shared, and how long it is kept. It states that it is not intended to result in policy recommendations.
Questions a shopper or store owner can ask
- Does the price change with the time of day or stock level, or only with the person viewing it?
- Does the site disclose what personal data feeds its pricing, and does the privacy policy match what it does?
- Is the same item priced differently in a private browser window, for a different account, or from a different location? Differences are a clue, not proof, since stores also run ordinary experiments and promotions.
- For a store: does a vendor tool use personal data, and which law covers the customers it reaches?
This article gives general information about published regulatory material. It is not legal advice, and it does not say that any named company prices unfairly.
FAQ
Is personalized pricing illegal?
Not by itself in the sources reviewed. New York requires a disclosure for it, and general rules on deceptive statements still apply.
Does the New York sentence appear on every online price?
No. It is required only when a price is set by an algorithm using the consumer's personal data and offered to a New York consumer, and the statute lists exemptions.
Did the FTC prove that stores charge people different prices?
The interim staff material described what data tools can use and what they can do. Because it relied on anonymized information, it offered hypothetical examples and did not name a specific price paid by a specific shopper.
What has Canada done about it?
The Competition Bureau opened a consultation with a discussion paper on June 10, 2025. The paper defines the terms and flags misleading statements about data as an issue, but it sets no new rule.
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Last verified: October 2026
Sources
- FTC Surveillance Pricing Study Indicates Wide Range of Personal Data Used to Set Individualized Consumer Prices, Federal Trade Commission, January 17, 2025
- Section 349-a, Personalized algorithmic pricing, New York General Business Law, New York State Senate, 2026
- Algorithmic pricing and competition: Discussion paper, Competition Bureau Canada, June 10, 2025
- National Retail Federation v. James, U.S. District Court for the Southern District of New York, decision of October 8, 2025, as reported by legal news coverage
- When Pricing Gets Personal, American Bar Association Antitrust Source, April 2026