Surveillance Pricing: They Know What You Want. Now, What Are They Going to Charge You?

Source: Silicon Bay Partners’ staff with assistance from ChatGPT
Photo: A sign warns customers that cameras are monitoring the parking lot of a Walmart store on January 17, 2017 in Skokie, Illinois. (Scott Olson/Getty Images)

Your loyalty card may not be saving you money. It may be teaching retailers how much more they can get out of you.

Remember when the price on the shelf was the price you paid at the register? Those were simpler times. You picked up a box of cereal, checked the price, and decided whether you could afford it. The supermarket didn’t need to know your shopping habits, your income bracket, your ZIP code or whether you were having a particularly stressful Tuesday.

Today, that old-fashioned transaction is colliding with a much more sophisticated business model: surveillance pricing. It involves using personal information, purchasing behavior, location and other data to influence the prices, discounts or products offered to individual consumers. The technology can help companies figure out not only what you want to buy, but also how much you might be willing to pay.

And that raises an uncomfortable question: Are companies competing to offer us the best price—or using what they know about us to determine the highest price we might tolerate?

Walmart’s Electronic Shelf Labels: Convenience or Something More?

Walmart has been rolling out electronic shelf labels, replacing traditional paper price tags with digital displays that can be updated centrally. The practical advantages are obvious: Employees can change prices more quickly, reduce the labor involved in replacing paper labels and potentially make fewer pricing errors.

But the technology also makes frequent price changes easier. And when a retailer can change thousands of prices remotely, consumers have legitimate questions about how those decisions are made.

Critics worry that electronic labels could eventually facilitate dynamic pricing, with prices changing according to demand, time or other market conditions. The more troubling possibility is personalized pricing, in which information about an individual shopper influences what that person pays.

Walmart, however, has publicly rejected that scenario. In September 2026, CEO John Furner said the company would not use personal information—including shopping history, income or perceived willingness to pay—to set individualized prices. Walmart says its electronic labels are about operational efficiency, not charging different customers different amounts for the same product.

That distinction matters. An electronic shelf label does not, by itself, mean a store is charging different shoppers different prices. A price displayed on a shelf is visible to everyone standing in the aisle.

Still, the technology makes rapid price changes possible. Consumers have every reason to want transparency about what triggers those changes, how often they occur and whether the prices remain consistent across stores and shopping channels.

After all, technology is only as reassuring as the rules governing its use.

Starbucks Rewards: The Price of Being a Regular

Then there’s Starbucks, where millions of customers voluntarily participate in a loyalty program designed to reward repeat business.

You buy your usual latte, scan the app, collect Stars and eventually redeem them for something free. It sounds like a straightforward bargain. But loyalty programs also give companies a detailed picture of customer behavior: what people buy, how often they visit, when they order, which promotions they use and how their spending changes over time.

That information can be valuable for more than deciding which coupon to send you.

A 2025 Washington Post investigation examined Starbucks Rewards data and found that promotional offers could vary with customers’ purchasing behavior. The reporting raised concerns that frequent customers might receive fewer offers during periods when they were already buying regularly, while other customers could receive incentives to encourage additional purchases.

That is not the same as proving Starbucks charged one customer more than another for the identical drink. It does, however, illustrate how data can influence the discounts and incentives a customer sees.

And that’s the catch: A company doesn’t necessarily have to raise your listed price to make your loyalty less rewarding. It can simply decide you don’t need a discount because its data suggest you’ll keep coming back anyway.

The customer who buys coffee every morning may be less likely to receive a coupon than the customer the company is trying to lure back. Loyalty, in other words, can become a signal that you’re willing to pay full price.

So much for being a VIP.

Your ZIP Code May Tell Them More Than You Think

Your ZIP code is more than a way to get the mail delivered. Combined with other information, it can help businesses infer neighborhood income levels, local demand, shopping patterns and the kinds of products customers may be interested in.

The Federal Trade Commission has been examining the use of personal data in what it calls surveillance pricing. Its January 2025 findings described how pricing intermediaries can use information such as location, demographics, browsing history and shopping behavior to influence the prices or promotions consumers see. The agency also described hypothetical scenarios in which a shopper’s ZIP code and behavior could affect which products appear in online search results.

That last point deserves attention. A ZIP code may help determine what products are promoted or what offers are shown, even when it does not directly change the price at checkout.

There are legitimate reasons for regional price differences. Shipping costs, local taxes, rent, labor expenses and competition can vary from one place to another. A store in an expensive urban neighborhood may have different operating costs from a store in a small town.

But a different question arises when companies use personal information to estimate what an individual customer can afford—or how urgently that customer needs something—and then tailor the offer accordingly.

Imagine two people searching for the same product. One is shown a bargain; the other sees a more expensive option because an algorithm believes that customer is less price-sensitive. Neither shopper necessarily knows the other received a different offer.

The concern is not that every ZIP-code-based price difference is discriminatory. It is that increasingly detailed consumer profiles could make it difficult to tell whether a price reflects the cost of doing business or the company’s estimate of how much it can extract from a particular customer.

The Loyalty Card Has a Memory

Supermarket loyalty cards were once marketed primarily as a way to save money. Sign up, scan your card, receive discounts. In exchange, the retailer learns what you buy.

Today, apps and loyalty accounts can connect purchases to a much larger digital profile. Depending on the company and its privacy practices, that profile may include online activity, location information, coupon use, purchase frequency and responses to earlier offers.

The Federal Trade Commission’s work has highlighted a broader market of technology companies that help retailers analyze consumer data and tailor pricing or promotions. These tools can use information supplied directly by customers, information inferred from their behavior and data obtained from other sources.

The business logic is straightforward. If a company knows you regularly buy a particular brand, it may not need to discount that product to keep you coming back. If it believes you’re shopping around, it might offer you a coupon. If you abandon an online cart, it might send a promotion designed to bring you back.

Some of that can benefit consumers. Personalized coupons can lower costs, and loyalty programs can offer genuinely useful rewards. The problem is that the same system can distribute benefits unevenly, based on what the company believes each customer needs to make a purchase—or how little incentive the customer needs at all.

A discount is welcome. A system that quietly decides who deserves one, and who can be charged more without noticing, is another matter.

Dynamic Pricing Is Not Always Surveillance Pricing

It is worth making a distinction. Prices have always changed. Airlines adjust fares, hotels charge different rates for different dates, and stores run promotions based on inventory and demand. Those practices are not automatically surveillance pricing.

The more specific concern is when personal data about an individual—or a profile of that person—is used to shape the price or offer presented to them.

The FTC’s investigation reflects concerns that this practice could undermine price transparency and fair competition. The agency’s work does not establish that every retailer is using individualized prices, nor does the existence of a patent or a new technology prove that a company has deployed it.

That is particularly relevant in the Walmart debate. Electronic labels make price updates easier, but they do not establish that Walmart is changing shelf prices based on individual shoppers. The company says it is not doing so.

Consumers should be able to scrutinize the technology without treating every potential use as a proven practice. The question is what retailers are doing with the systems they have—and what safeguards prevent them from going further.

Who Is Watching the Watchers?

The deeper issue is the imbalance of information.

Retailers can collect and analyze enormous amounts of data about customers. Consumers, meanwhile, may have little idea what information has been assembled about them, which outside companies have access to it, or how it affects the offers they see.

That makes meaningful transparency essential. If personal data are being used to determine prices or discounts, consumers should be told. They should be able to understand the factors involved, challenge deceptive practices and compare prices without having to guess whether an algorithm has put a thumb on the scale.

Loyalty programs should not require customers to surrender privacy without a clear understanding of the bargain. And digital shelf labels should not become a black box in which prices change without a clear explanation.

There is also a simple fairness question: Should two people shopping for the same item face different prices because one has been profiled as more affluent, more loyal, more desperate or less likely to comparison-shop?

Companies will argue that personalization makes commerce more efficient and helps deliver relevant offers. Sometimes it does. But efficiency for the seller does not automatically mean fairness for the buyer.

The burden should not fall entirely on consumers to clear their cookies, avoid every loyalty program, shop anonymously and compare prices across a dozen websites just to know whether they’re getting a fair deal.

Ventured’s Take

The next time you scan a loyalty card, open a retailer’s app or walk past a digital shelf label, remember that the transaction may generate information that outlasts the purchase itself.

Your coffee order can reveal a routine. Your grocery cart can reveal preferences. Your ZIP code can provide clues about your neighborhood. Your browsing behavior can suggest what you want, what you can afford and how urgently you need it.

None of that proves a company is charging you more because of who you are. But it does explain why surveillance pricing deserves scrutiny.

The promise of technology is that it can make shopping easier and prices more competitive. The danger is that it can also make the customer easier to profile—and the price harder to question.

We used to ask, “How much does it cost?”

Now we may have to ask a second question:

“How much does it cost me—and how did the company decide I should pay that much?”