Name Your Price...With Your Personal Data: How New York's Tackling Algorithmic Pricing

Root of the Matter

• New York's Algorithmic Pricing Disclosure Act now requires any entity using personalized algorithmic pricing in the state to display the disclosure, "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA," with violations subject to injunctions and civil penalties of up to $1,000.

Real-World Consumer Moment

You and your friend are online shopping together, laughing over FaceTime from opposite coasts. You pull up the same item they're excited about, but something doesn't add up. Your screen shows $80.00. Theirs shows $65.00. Same product, same moment. Different price.

The only thing separating you is 2,000 miles and the data trails tied to your zip codes.

That's algorithmic pricing, a model dynamically adjusting what price you see based on the data it collects from you, shaping your everyday choices.

Inside the Company

On the backend of things, product and privacy teams are staring at dashboards, cost models, regional demand curves, and machine-generated "optimizations." To them, it's efficiency: matching market behavior, keeping margins healthy, reducing return rates aligned with consumer expectations.

Now, they're also under growing pressure to ensure they've properly mapped how personal data moves through pricing tools, flagging all the places a price is tailored to an individual, and deciding whether that logic needs to be segregated for New Yorkers and building out the "how," including workflows, triggers, and system changes.

Some teams might view this obligation as unduly stigmatizing, even confusing and possibly triggering consumer distrust, when the team believes the workflow has always been ordinary.

Most teams don't have someone mapping the full picture across legal, product, data, UX. That's exactly where things start to break. Just blinders on the metrics they're responsible for to get through their day.

Pulse Check for Product & Privacy Teams

• Does your product team know whether their pricing model uses personal data?

• Do you know who owns the data flow map?

• Can you isolate the NY model without breaking pricing across the board?

• Does your team know where the disclosure belongs and when and where to prompt and track it?

• Who is responsible for ongoing updates if and when this law shifts again? How will that accountability be tracked?

Overview and History

The New York Algorithmic Pricing Disclosure Act, New York Gen. Bus. Law § 349-A, was signed into law on May 9, 2025, as part of the state budget. It imposes disclosures obligations on any entity doing business in New York that uses personalized algorithmic pricing directed towards New York consumers. The law went into effect on July 8, 2025, but enforcement was paused when the National Retail Federation (NRF) sued to block the state law. Enforcement was held until November 10, 2025.

The NRF challenged the law on First Amendment grounds, arguing the disclosure compels speech. On October 8, 2025, Judge Rakoff in the U.S. District Court for the Southern District of New York, upheld the law as constitutional and found that the disclosure was "purely factual" and uncontroversial, requiring a review that was reasonably related to the state's legitimate interest in preventing consumer deception without being unduly burdensome.

On November 5, 2025, New York Attorney General James urged New York consumers to report observed undisclosed algorithmic pricing, signaling the start of potential active enforcement.

Covered Businesses Using or Considering Using Algorithmic Pricing Technology

The term "entity" is broadly defined and captures businesses either located in or doing business in New York using algorithmic pricing that relies on personal data. To paint a picture, this could be an online retailer using a pricing plugin adjusting prices based on browsing history of a New Yorker or a small business located in New York using a third-party tool varying prices by customer profile.

"Personal data" means "any data that identifies or could reasonably be linked, directly or indirectly, with a specific consumer or device." Think device IDs used to recognize returning visitors, click, scroll, or purchase behavior tied to a consumer's profile.

Location data used for mileage- and duration-based pricing by for-hire vehicles is carved out.

Obligations

• Mandatory clear and conspicuous disclosure on or near the personalized price, stating: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” presented contemporaneously with the price and in letter and wording easily visible and understandable to the average consumer

Exemptions

• Entities regulated under state insurance law

• Regulated financial institutions

• Discounted prices offered under existing subscription-based agreements for the same goods or services

Enforcement

• The New York Attorney General may issue cease and desist notices, seek injunctive relief, and pursue civil penalties up to $1,000 per violation.

• No private right of action, though determined plaintiffs may test creative product tort liability theories.

Uncover Business Blind Spots

• Audit how personal data informs pricing. Most teams discover inputs they didn't realize were feeding the model

• Confirm whether your model is "personalized" under the statute

• Document your data inputs for New York scrutiny

• Identify who owns the long-term governance for updates and how they will be accountable. These questions usually uncover gaps that weren't visible until someone walked through the entire workflow with fresh eyes

Consumer Pro Tips

• Check prices in Incognito mode or with a VPN

• Test prices and discounts across devices and screenshot evidence

• Watch for zip code-based differences

• Consider reporting undisclosed pricing to NY AG's office

Our Grounded Take

This is a preview of what's coming - pricing transparency, AI disclosures, focus on surveillance pricing, and consumer-centric design as emerging regulatory norms. Companies that build strong governance now can adapt more smoothly later instead of rebuilding under pressure.

If you're building or refining your pricing workflows, this is the moment to get intentional about data mapping, cross-team alignment, and sustainable compliance routines.

A Grounded Reader's Note and Disclaimer:

This material is provided for general information only and is not intended to constitute legal advice. It should not be relied upon as a substitute for obtaining legal advice tailored to your specific circumstances. You should consult with qualified counsel about your individual situation. Certain portions of this blog may be considered attorney advertising. We strive to ensure the information presented is current, complete, and accurate, but mistakes may occur. Grounded Legal Practice, PLLC and its authors make no representations, warranties, or guarantees regarding completeness, accuracy, or suitability of this material and assume no responsibility for any errors or omissions.