The Tool Desk
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The term is still developing. The Federal Trade Commission (FTC) has said descriptions vary and has not adopted one single technical definition, while California’s attorney general has described it as using personal information to set targeted, individualized prices. The practical question is whether data about you, rather than only market conditions, influences what you are charged or offered.
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What surveillance pricing means
At its broadest, surveillance pricing describes a data-driven system that observes or obtains information about consumers, draws conclusions about them, and uses those conclusions to customize a commercial offer. Customization can affect the number beside a product, but it can also affect which products appear first, which promotion is displayed, whether an offer is available, or which version of a service is presented.
The FTC’s January 2025 Issue Spotlight describes an ecosystem in which large-scale data collection helps sellers customize both prices and the selection of goods or services offered to each consumer. The spotlight also says that descriptions of surveillance pricing differ and does not formally or concretely define the term. In a January 2026 release, California Attorney General Rob Bonta gave a more direct description: personal information is used to set targeted, individualized prices, so people buying the same thing at the same time from the same business may receive different prices.
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Those descriptions point to a useful test: is personal information or an inference about a consumer being used to individualize the price or offer? If the answer is yes, the practice fits the usual policy meaning of surveillance pricing. If a seller is responding only to demand, inventory, time, or another market-wide condition, it is generally ordinary dynamic pricing instead.
How the process can work
1. Data is collected or obtained
A seller may use information it collected directly, information supplied by another company, or predictions produced by an analytics or pricing intermediary. Examples discussed by the FTC include location, demographic information, browsing patterns, shopping history, webpage mouse movements, and products left in an online cart. The list describes possible inputs, not a checklist used by every retailer.
Some signals are obvious, such as an account’s previous purchases. Others are behavioral, such as how long someone pauses over a product or whether a shopper repeatedly returns to a checkout page. Data can also be combined with inferred characteristics—for example, an estimate of a shopper’s budget, urgency, or likelihood of completing a purchase.
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Pricing and analytics firms can combine personal data with inferred information, place shoppers into categories, predict behavior or willingness to pay, and provide recommendations to a business. In the FTC’s description, these intermediaries may work on pricing, discounts, product rankings, or availability rather than only on a single numeric price.
A model might estimate that one visitor is highly likely to buy immediately, while another is price-sensitive and may respond to a coupon. The business could then show different promotions or rank different products. A data intermediary may not make the final retail decision, but its scores or recommendations can shape what the retailer displays.
3. The system selects a price or offer
The output may be a higher or lower price, a targeted discount, a different bundle, a product recommendation, or a change in which inventory is visible. The FTC’s 2025 release said the same product may be presented with different prices or promotions based on consumer-related data and behavior as well as location, time, and purchasing channel.
That means surveillance pricing is not limited to a webpage showing two different numbers. A shopper could pay the same listed price as someone else but receive a smaller coupon, see a less favorable bundle, or be steered toward a more expensive product. In some systems, what a person is shown or allowed to buy may be as important as the price itself.
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4. The system may learn from the response
When a shopper clicks, abandons a cart, uses a coupon, or completes a purchase, that response can become another data point. A model may be updated over time, although the available public descriptions do not establish how any particular retailer updates its models or how often. Do not assume that every business uses continuous, individual experimentation.
A hypothetical example, not a documented incident
The FTC gave a hypothetical example in which a person profiled as a new parent might be shown higher-priced baby thermometers in search results. The example illustrates how profiling could change product selection. It is not evidence that a real parent was charged a particular amount, and the FTC says examples in the staff perspective were hypothetical while the study’s released information was aggregated or anonymized.
Surveillance pricing versus ordinary dynamic pricing
Dynamic pricing changes prices in response to conditions such as supply, demand, inventory, timing, or a purchasing channel. Airlines, hotels, event sellers, and many online retailers can adjust prices as conditions change without using an individual shopper’s profile. Surveillance pricing uses personal information to target an individual or a group with individualized pricing or offers. A system can use both approaches at once.
| Question | Ordinary dynamic pricing | Surveillance pricing |
|---|---|---|
| Primary input | Supply, demand, inventory, timing, or other market conditions | Personal information, behavior, or inferences about a consumer |
| Typical output | A market-wide or condition-based price change | An individualized price, discount, ranking, product selection, or availability decision |
| Who may see the result | People shopping under the same market conditions may see the same change | Different consumers may receive different treatment for the same product and time |
| What a price difference proves | A difference over time can be explained by changing conditions | A difference is meaningful only if evidence connects it to personal-data targeting |
A time-based price change alone is not proof of surveillance pricing. Location can also be ambiguous: a different tax, delivery cost, currency, or regional market may explain a difference without an individualized profile. To establish surveillance pricing, investigators generally need evidence about the data used and the mechanism that generated the offer.
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What regulators and investigations have found
FTC study of pricing intermediaries
In July 2024, the FTC issued study orders to intermediary firms. Its January 17, 2025 release described an initial analysis of documents supplied by Mastercard, Accenture, PROS, Bloomreach, Revionics, and McKinsey & Co. FTC staff said the intermediaries examined worked with at least 250 clients, including businesses in grocery and apparel.
The finding concerns the intermediary ecosystem and its clients that were studied. It does not prove that every retailer uses individualized prices, that every client used every available data signal, or that every price difference came from personal information. The FTC said the study was still ongoing at the time of that release.
Instacart investigation cited by California
California Attorney General Rob Bonta’s January 27, 2026 release summarized a 2025 Consumer Reports investigation of Instacart grocery shopping. According to the state release, some per-item prices in the investigation differed by as much as 23% from one customer to another. The observed differences ranged from seven cents to $2.56 per item.
These figures are attributed to Consumer Reports as relayed by California’s attorney general. They describe that investigation, not all online grocery shopping. The same state release says Instacart publicly stated that it had stopped offering technology that allowed grocery retailers to charge different shoppers different prices for the same groceries at the same time. The figures therefore should not be presented as proof that the practice is currently operating across Instacart or across the retail market.
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Individualized pricing can change the economic relationship between a shopper and a seller. A consumer may reasonably expect a listed price to be the price available to other shoppers under the same conditions. If a business quietly estimates how much a particular person will pay and adjusts the offer accordingly, the consumer may have no practical way to recognize or challenge the difference.
Personalized selection can matter even when the checkout price is identical. Ranking a premium product above a cheaper equivalent, withholding a promotion, or limiting which inventory appears can influence the final purchase. The FTC’s spotlight therefore treats surveillance as affecting both the price and the selection of goods or services.
Concerns also depend on context. A difference could reflect legitimate regional costs, a broadly available loyalty benefit, a time-limited sale, or a transparent segment-wide promotion rather than covert individual targeting. The central issues are the data used, the scope of the targeting, the transparency provided, and the law that applies where the consumer and business operate.
Current United States regulatory picture
Federal policy remains a draft position
As of October 13, 2026, the FTC had announced a draft enforcement policy statement on personalized pricing and sought public comment, with a stated comment deadline of September 18, 2026. The FTC described personalized pricing as using personal data to set a price according to how much a company believes a particular consumer will spend.
The agency said it cannot ban the practice in all circumstances. It also said that undisclosed use of personal data to set prices may violate the FTC Act or other laws it enforces. This is a draft enforcement position announced for comment, not a categorical nationwide prohibition. Whether a practice is unlawful depends on the facts, the disclosures, and the other legal rules that apply.
California’s inquiry
In January 2026, Attorney General Bonta announced an investigative sweep focused on retail, grocery, and hotel businesses. The state said personalized price-setting may trigger obligations under the California Consumer Privacy Act, including its purpose-limitation principle. That principle restricts use of personal information to purposes consistent with consumers’ reasonable expectations.
The announcement describes an inquiry and potential compliance issues. It is not a final finding that all surveillance pricing violates California law. Businesses and consumers outside California may face different rules, and legal obligations can change as agencies issue guidance, complete investigations, or adopt new regulations.
How to assess a suspicious price difference
Seeing two prices is a reason to investigate, not proof of surveillance pricing. Work through the following checks before drawing a conclusion:
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- Record the product, seller, exact time, currency, shipping destination, membership status, and purchasing channel.
- Compare the same item while signed out and signed in, but treat the result as an observation rather than proof of causation.
- Check whether taxes, delivery charges, regional inventory, exchange rates, a coupon, or a loyalty program explains the difference.
- Compare the seller’s website with its mobile app, a physical store, or another authorized channel.
- Save screenshots and receipts if the difference affects a substantial purchase or appears repeatedly.
- Look for a privacy notice or promotion terms explaining personalization, eligibility, or data use.
A VPN, private browsing, or a different device may change some data signals, but the FTC’s August 2026 announcement does not establish that these methods reliably prevent individualized prices. A changed result could reflect a different cookie, login state, location estimate, inventory cache, or ordinary price movement.
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Compare sellers and channels
Search for the same model or service through more than one seller and, where practical, compare the web, app, and in-person channel. Keep the comparison fair by matching taxes, shipping, service fees, membership benefits, quantity, and delivery time.
Review privacy choices
Read the retailer’s privacy controls and account settings. Limit optional tracking or data sharing where the service allows it, and avoid supplying information that is not needed for the transaction. These choices may reduce some signals but cannot guarantee that a seller lacks other information or that prices will become identical.
Use a private session as a diagnostic
Testing a logged-out or private-browsing session can reveal whether the experience changes when some account or cookie data is absent. Treat it as a diagnostic comparison, not a guaranteed defense. A retailer may still use location, device, channel, inventory, or information obtained from another source.
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For a material discrepancy, ask customer support which factors determine the price or promotion and whether a loyalty, regional, or channel rule applies. Keep the response with your records. A refusal to explain does not itself prove unlawful surveillance pricing, but a clear answer can distinguish a published promotion from an opaque individualized offer.
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Report possible violations
Consumers can preserve evidence and contact the appropriate state consumer-protection office or federal agency when they believe a business used personal information deceptively or outside the promises in its privacy notice. Complaints are most useful when they include dates, screenshots, account status, location, product identifiers, and the exact prices shown.
Common misconceptions
“Every different price is surveillance pricing.”
No. Prices can differ because of time, demand, inventory, taxes, shipping, currency, membership terms, or a different purchasing channel. Personal-data targeting must be connected to the difference.
“Dynamic pricing and surveillance pricing are opposites.”
No. A business can adjust a base price for demand and then apply a personal discount or ranking. The mechanisms can overlap.
“A regulator’s hypothetical example proves the practice occurred.”
No. The FTC’s new-parent thermometer example was hypothetical. It explains a possible mechanism, not a documented transaction involving a real shopper.
“The United States has banned surveillance pricing.”
No universal federal ban is established by the cited 2026 materials. The FTC position was at the draft-and-comment stage, and California had announced an inquiry rather than a final statewide finding covering every business.
Bottom line
Surveillance pricing is best understood as personal-data-driven individualization: a seller uses information or inferences about a consumer to shape the price, discount, product ranking, selection, or availability that consumer receives. Dynamic pricing based only on market conditions is different, although both systems can operate together. Current findings show that pricing intermediaries and at least one investigated grocery-shopping context warrant scrutiny, not that every retailer charges every shopper a secret personalized price. Consumers can compare channels, review privacy controls, and document discrepancies, while recognizing that no single browser setting or privacy tool has been shown to guarantee protection.
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