Have you ever wondered whether the price you see online is the same price everyone else sees?
With the growth of artificial intelligence, data tracking, and personalized marketing, that question is becoming increasingly important. A practice known as surveillance pricing allows companies to use information about consumers to influence the prices, discounts, products, or promotions they see.
The Federal Trade Commission (FTC) has been investigating the practice, and in 2025 reported that companies providing pricing technology can use surprisingly detailed information about consumers, including browsing history, location, shopping behavior, and even activity such as mouse movements on a website.
For bargain hunters, that creates an uncomfortable possibility: the price on your screen may not always be determined solely by what an item costs or how much demand there is for it. It could potentially be influenced by what a company knows about you.
What Is Surveillance Pricing?
Surveillance pricing generally refers to using data collected about consumers to help determine the prices or offers presented to them.
The FTC has also used the term personalized pricing, defining it as using personal data to set prices based on how much a business believes an individual consumer is willing to spend.
Imagine two people shopping online for the exact same product.
One shopper frequently compares prices, uses coupons, abandons shopping carts, and visits competing websites before buying.
Another shopper regularly purchases immediately without comparing prices.
If a retailer’s pricing system uses that behavioral information to offer the first shopper a $10 discount while showing the second shopper the regular price, that would be an example of personalized or surveillance-based pricing.
The concept isn’t entirely new. Sellers have always known that different customers may be willing to pay different amounts. What’s different today is the enormous amount of consumer data that can be collected and analyzed automatically.
Surveillance Pricing vs. Dynamic Pricing
It’s important to distinguish surveillance pricing from dynamic pricing.
Dynamic pricing changes prices based primarily on market conditions. Airline tickets are a familiar example. Prices may increase as seats disappear or a departure date approaches. Hotels, rideshare services, event tickets, and other businesses may also adjust prices based on demand, availability, location, or timing.
Surveillance pricing goes a step further by incorporating information about the consumer.
Instead of asking:
“How much should we charge for this product right now?”
the algorithm may effectively ask:
“How much might this particular shopper be willing to pay?”
The FTC notes that surveillance pricing can overlap with dynamic pricing and other established pricing methods, which can make the practice difficult for consumers to identify.
What Information Could Be Used?
Modern retailers and their technology providers potentially have access to an enormous amount of information.
The FTC’s investigation found that pricing intermediaries can have access to direct consumer information, inferred information, and data obtained from both first-party and third-party sources.
Depending on the company and technology involved, information used by pricing or marketing systems could include:
- Your approximate or precise location
- Browsing and search history
- Previous purchases
- Items you’ve viewed
- Items you’ve left in your shopping cart
- Demographic information
- Device or shopping channel
- Interactions with a website
- Information purchased or obtained from third parties
The FTC’s initial findings even identified mouse movements on webpages as one type of consumer behavior that can be tracked and potentially incorporated into retail personalization systems.
That doesn’t mean every retailer is using all of this information to change prices. The technology, however, increasingly makes sophisticated personalization possible.
Could You Actually Pay More Because of Your Data?
Potentially.
The FTC began studying surveillance pricing technologies in 2024 and requested information from eight companies about products and services that could combine artificial intelligence, algorithms, and consumer information to target prices.
In January 2025, the agency released initial findings indicating that pricing intermediaries could use detailed consumer data to customize prices, discounts, and even which products shoppers see. The companies examined worked with at least 250 clients across industries including grocery and apparel.
The findings don’t mean that every retailer using these companies is secretly charging every customer a different price. The FTC described examples in its report as hypothetical because confidential company information was aggregated or anonymized.
But they demonstrate that the technology exists to make highly individualized pricing possible.
Sometimes Personalization Could Save You Money
Personalized pricing isn’t automatically bad for consumers.
A retailer might use shopping behavior to send a discount to someone who appears unlikely to purchase at full price. Loyalty programs have operated on a similar principle for years, offering different customers different coupons and promotions.
A shopper who repeatedly abandons an item in a cart might receive a coupon encouraging them to finish the purchase.
Personalized offers can therefore work in your favor.
The concern arises when personalization becomes invisible and consumers don’t know that their data is influencing what they pay.
Why Surveillance Pricing Is Controversial
Price comparison works best when shoppers know what something actually costs.
If everyone sees roughly the same price, you can check several stores and determine which has the best deal.
Surveillance pricing could complicate that process because the price might depend partly on who’s looking.
There’s also a privacy issue. Many shoppers probably expect retailers to remember their purchases or recommend products they might like. They may be less comfortable discovering that browsing behavior or other personal information could potentially help determine the price they’re offered.
In August 2026, the FTC proposed an enforcement policy addressing personalized pricing. The agency said businesses may risk violating federal law when consumers reasonably expect prices not to vary according to personal data and companies fail to clearly disclose that personalization and its basis. The FTC also noted that it does not have authority to prohibit personalized pricing in every circumstance.
How to Protect Yourself From Personalized Pricing
You probably can’t completely prevent companies from collecting or using data about you, but you can make comparison shopping a little more revealing.
Compare prices before buying. Check the same product at multiple retailers instead of assuming the first price you see is competitive.
Try a private browsing window. Open the product in an incognito or private browser window where you’re not logged into your account. The FTC itself has noted private browsing as one step consumers might use to try to avoid higher personalized prices.
Compare logged-in and logged-out prices. If possible, check a price before signing into your account and again afterward.
Check another device. Looking at the same product on another phone, tablet, or computer can sometimes reveal differences in promotions or offers.
Clear cookies periodically. Cookies are one way websites recognize returning visitors and track activity, although deleting them won’t eliminate every form of tracking.
Limit unnecessary location access. Review which shopping apps have permission to access your location and whether they really need it.
Don’t assume a personalized offer is the best deal. “Just for you” sounds enticing, but compare the final price with other retailers before buying.
Don’t Confuse Every Price Change With Surveillance Pricing
Seeing a price change doesn’t prove you’ve encountered surveillance pricing.
Prices fluctuate for countless reasons, including inventory, sales, demand, competitor pricing, time of day, geographic markets, shipping costs, and promotional campaigns.
If your airline ticket costs more today than yesterday, that doesn’t necessarily mean the airline studied your browser history and decided you would pay another $50.
The defining issue with surveillance pricing is the use of personal information or inferred characteristics about a consumer to influence the price or offer presented to that consumer.
The Future of Shopping May Be More Personalized
Online shopping has already become incredibly personalized.
Retailers can recommend products based on previous purchases, display advertisements based on browsing history, send customized coupons, and predict what someone might buy next.
Pricing may be the next frontier.
The FTC’s investigation reflects growing regulatory interest in where personalization crosses the line from useful marketing into potentially unfair or deceptive treatment of consumers. As of 2026, federal regulators are continuing to examine how existing consumer-protection laws apply to personalized pricing.
For consumers, the old money-saving advice of comparison shopping may become more important than ever.
The difference is that you may eventually need to compare not only one store against another, but also one version of yourself against another.
Bottom Line
Surveillance pricing uses information about consumers to potentially customize the prices, discounts, or offers they receive.
It doesn’t necessarily mean you’re being charged more, and personalized offers can sometimes save you money. The bigger issue is transparency: shoppers may not know when their data is influencing what appears on their screens.
Until pricing practices become more transparent, treat online prices as offers rather than universal price tags. Compare retailers, check prices while logged out or browsing privately, and pay attention when a supposedly personalized deal isn’t much of a deal at all.
Your shopping history can be valuable data. Increasingly, knowing how that data may be used could become another tool in your money-saving toolbox.
