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Surveillance pricing is the use of personal information or inferences about a shopper to tailor the price, discount, product ranking, availability, or selection that shopper sees. A seller might use data such as location, browsing behavior, purchase history, demographics, or activity on a webpage to estimate what a particular person may pay. The term is still developing: the Federal Trade Commission (FTC) says descriptions differ, and its January 2025 staff spotlight did not establish one formal technical definition.
It overlaps with dynamic pricing, but the trigger is different. Dynamic pricing responds to market conditions such as demand, inventory, timing, or supply. It becomes surveillance pricing when information about an individual consumer is used to customize the amount or offer. A price changing between Tuesday and Wednesday, by itself, does not show that a personal profile was used.
What surveillance pricing means
The FTC describes surveillance pricing as an ecosystem in which extensive data collection helps sellers customize both prices and the selection of goods or services offered to each consumer. California Attorney General Rob Bonta’s January 2026 description is more direct: a business uses personal information to set targeted, individualized prices, so two people buying the same thing from the same business at the same time could receive different prices.
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Neither description should be treated as a settled, universal definition. “Surveillance pricing” is a policy term used to describe a range of data-driven practices. Depending on the system, personalization may affect the price itself, a coupon, the order in which products appear, whether an item is shown, or which inventory a customer is permitted to see.
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The central question
To evaluate a pricing practice, ask: Did information about this consumer, or a group to which the consumer was assigned, influence the price or commercial offer? If the answer is yes, the practice fits the commonly used meaning of surveillance pricing. If the price changed only because demand, inventory, or time changed, it is ordinary dynamic pricing unless additional evidence shows personal targeting.
How the process can work
Most systems are not a single “personal price” switch. They can involve a retailer, an outside analytics or pricing intermediary, and several data feeds. The FTC’s 2025 materials describe intermediaries that combine information, infer characteristics, categorize shoppers, predict behavior or willingness to pay, and then recommend or deliver an individualized result.
- Collect signals. A website or partner may receive location, demographic information, browsing patterns, shopping history, webpage mouse movements, or products left in an online cart. The FTC lists these as examples, not as a claim that every retailer uses every signal.
- Combine and infer. Data can be joined with information from other sources. A system may infer a shopper’s household situation, urgency, likelihood of completing a purchase, or estimated willingness to pay. An inference can matter even when the shopper never directly supplied that characteristic.
- Assign a segment or score. The shopper may be placed in a category, such as a price-sensitive visitor, a likely repeat buyer, or a customer predicted to accept a higher price. The category can be broad or individualized.
- Choose the commercial result. Software can select a price, discount, product ranking, search result, inventory pool, or availability rule. It may also decide which promotion is displayed rather than changing the base price.
- Deliver and measure. The system presents the result through a website, app, email, marketplace, call center, or another purchasing channel. Subsequent clicks, purchases, and abandoned carts can become new inputs.
Location, time, and purchasing channel can also affect a displayed result. Those factors do not automatically make a practice surveillance pricing; the important issue is whether personal information or an inferred characteristic is used to individualize the result.
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| Element shown to a shopper | Possible effect | Why it matters |
|---|---|---|
| Price | A higher or lower amount for the same product or service | The clearest example of individualized pricing |
| Discount or coupon | A promotion offered to one shopper but not another | The final amount can differ even when the listed price is identical |
| Product ranking | Some products appear first in search results | Profiling can steer a shopper toward a more expensive option |
| Availability | A shopper sees different inventory, delivery choices, or access rules | Personalization can change what a person is allowed to buy, not only the price |
| Product selection | The system presents a different set of goods or services | Choice architecture can influence spending without a visible price change |
A regulator’s hypothetical example
The FTC staff perspective used a hypothetical case in which a person profiled as a new parent might be shown higher-priced baby thermometers in search results. This illustrates how profiling could alter product selection. It is not evidence that a real parent was charged a particular amount, and the FTC said the examples in that perspective were hypothetical. The agency published aggregated or anonymized information from its study rather than individual customer records.
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Surveillance pricing versus dynamic pricing
Both practices can produce different prices, but they answer different questions. Dynamic pricing asks what market conditions justify charging now. Surveillance pricing asks what the seller predicts this particular consumer, or a consumer segment, will accept.
| Comparison point | Dynamic pricing | Surveillance pricing |
|---|---|---|
| Main input | Supply, demand, inventory, timing, capacity, or other market conditions | Personal information, behavior, or inferred characteristics |
| Who receives the result? | Often everyone shopping under the same market conditions, though prices can vary by channel or time | An individual or selected segment based on a profile |
| What changes? | Usually the listed price, sometimes availability | The price, discount, ranking, availability, or product selection |
| Evidence needed | Records showing a market or operational change | Evidence that personal data or an inference affected the outcome |
| What a price difference proves | It may show only that prices changed over time or across channels | It may support individualized targeting only when linked to data use |
The mechanisms can overlap. A retailer might change prices because demand is high and then use a profile to decide which shoppers receive a discount. Conversely, two customers may see different amounts because they are in different locations or purchasing through different channels, without any individualized willingness-to-pay analysis. A price difference alone does not establish surveillance pricing.
What regulators and investigations have found
The FTC’s intermediary study
In July 2024, the FTC issued study orders to pricing and analytics intermediaries. 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 studied worked with at least 250 clients, including businesses in grocery and apparel.
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These findings concern the intermediary ecosystem and the clients represented in the study. They do not prove that every retailer uses individualized prices. The FTC said the study was still ongoing when that release was issued. Its materials describe capabilities and practices identified in submitted documents, not a finding that every use of those capabilities is unlawful.
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The Instacart investigation cited by California
In a January 27, 2026 release, California Attorney General Rob Bonta summarized a 2025 Consumer Reports investigation of grocery shopping on Instacart. The state release said the investigation observed per-item differences of as much as 23% from one customer to another, with observed differences ranging from seven cents to $2.56 per item.
Those figures are attributed to Consumer Reports as relayed by the California Attorney General. They describe the investigated examples, not all grocery transactions or all retailers. The same California release said 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 continues on that service.
Where the law and policy stand in 2026
Federal policy: a draft enforcement 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 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 warned that undisclosed use of personal data to set prices may violate the FTC Act or other laws it enforces. Because the statement was presented for comment, it is a draft enforcement position rather than a categorical nationwide prohibition. The legal result can depend on disclosure, the data involved, the conduct, and the jurisdiction.
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FTC Chairman Andrew Ferguson summarized the consumer expectation at issue: “When consumers see a listed price, they expect it to be same price that everyone else sees, not the retailer’s estimate of how much they are willing to pay based on their personal data.” That is an attributed regulator view, not an adjudicated finding that every personalized price is illegal.
California’s inquiry
In January 2026, Attorney General Bonta announced an investigative sweep focused on retail, grocery, and hotel businesses. California 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, not a final conclusion that all surveillance pricing violates California law. Bonta said, “Practices like surveillance pricing may undermine consumer trust, unfairly raise prices, and when conducted without proper disclosure or beyond reasonable expectations, may violate California law.” The statement expresses the attorney general’s position while the investigation and legal analysis proceed.
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No single consumer action reliably proves or prevents surveillance pricing. The most useful approach is to reduce uncertainty, compare the transaction, and understand what each privacy measure can and cannot accomplish.
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1. Compare the same item across channels
Check the seller’s website, app, logged-out view, and other legitimate purchasing channels when practical. Compare the same product, quantity, shipping terms, taxes, membership status, and time. Record the date and the final checkout amount. A difference is a reason to investigate, not proof that profiling caused it.
2. Review privacy and account choices
Read the retailer’s privacy notice and account settings for information about targeted advertising, sharing, personalization, and data retention. Where the law provides an opt-out or access request, use the retailer’s stated process and keep a copy of the request. An opt-out may affect advertising or data sharing without guaranteeing a uniform price.
3. Try privacy-reducing browsing measures cautiously
The FTC’s August 2026 announcement said its draft statement noted that consumers might consider a VPN, private browsing, or avoiding retailers engaged in personalized pricing. These measures may limit some signals, such as an account cookie or a visible location, but the cited announcement does not demonstrate that they reliably prevent individualized prices. A retailer may still recognize an account, use purchase history, or rely on other data.
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Coupons, delivery fees, service charges, membership benefits, taxes, and minimum-order rules can create legitimate differences. Save the product page and checkout screen if you believe the result changed unexpectedly. Do not treat a personalized promotion as evidence of a different base price unless the records show that distinction.
5. Ask the seller a precise question
Instead of asking whether prices are “dynamic,” ask whether personal information or inferred characteristics are used to set prices, select discounts, rank products, or determine availability. Ask which categories of data are used, whether third parties provide them, and how to exercise applicable privacy rights. A general customer-service answer may not resolve the issue, but a specific question creates a clearer record.
Common mistakes when interpreting price differences
- Confusing time with identity: A price that changed overnight may reflect inventory or demand rather than a customer profile.
- Assuming a cookie changed the price: A logged-in and logged-out comparison can reveal a difference, but it does not identify the underlying cause.
- Treating a targeted coupon as a higher base price: Two shoppers may face the same list price while only one receives a discount.
- Generalizing from one investigation: The FTC findings concern studied intermediaries and clients; the California release relays a specific Consumer Reports investigation.
- Overstating privacy tools: VPNs and private browsing can change some signals but are not demonstrated, universal fixes.
- Calling every personalization practice illegal: The FTC policy statement was a draft for comment, and California announced an inquiry rather than a blanket ban.
How to evaluate a suspected case
- Define the comparison: identical item or service, same quantity, same taxes and fees, same time window, and same purchasing channel.
- Capture the evidence: screenshots, account state, location settings, coupon status, and the final checkout total.
- Repeat the comparison without changing multiple variables at once. Changing location, device, account, and time together makes the result difficult to interpret.
- Look for a documented market explanation, such as a sale ending, inventory changing, or a delivery fee being recalculated.
- Ask whether personal data could plausibly have influenced the result and request an explanation or applicable privacy-rights process from the seller.
- Escalate through the relevant consumer-protection or privacy authority only after preserving the records and identifying the jurisdiction.
Why the distinction matters
Surveillance pricing can redistribute the cost of a transaction according to what a seller believes a person will tolerate, while also shaping what that person sees. That creates questions about transparency, reasonable consumer expectations, privacy purpose limits, discrimination, and the ability to compare offers fairly. At the same time, evidence must be specific: a different price is not enough to identify the data source, the algorithm, or an unlawful practice.
The practical test is therefore two-part. First, establish whether the commercial result differed. Second, establish whether personal information or an inference about the shopper caused that difference. The first can often be documented by comparison; the second generally requires disclosures, records, technical evidence, or a regulator’s investigation.
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