States are banning 'surveillance pricing' — but the reality is more complicated than the name suggests

When Colorado's legislature passed a bill this summer banning companies from using customers' personal data to set individualized prices, it looked like a straightforward consumer-protection win. Then Gov. Jared Polis vetoed it.

Many Coloradans won't get discounts on items they buy if I were to sign this. It would punish differentially lower prices, not just higher prices.— Jared Polis, Colorado Governor

The veto cracked open a fault line running through one of the fastest-moving consumer-protection debates in the country. Americans are directing their anger over high prices, AI, and corporate data collection at a practice called 'surveillance pricing' — and lawmakers at every level are responding. But the same algorithm that can charge one shopper more than another can also deliver that shopper a discount, and broad bans may not distinguish between the two.

At its core, surveillance pricing draws on personal data — browsing activity, precise location, purchase history, device information, and inferred demographics — and feeds it through algorithms to arrive at a price tailored to a single consumer. McDonald Hopkins describes the objective simply: determine the most a given customer will pay and charge exactly that. This is distinct from ordinary dynamic pricing, where a storewide sale or demand-based surge adjusts prices for everyone equally.

The scale of the practice snapped into focus in late 2025, when a joint investigation by several consumer advocacy groups revealed that a major online grocery delivery platform had been conducting large-scale, AI-enabled pricing experiments on customers who had no idea they were being tested. Researchers followed more than 400 shoppers across four U.S. cities and discovered that nearly three-quarters of grocery items carried different prices for different customers — even when those customers were placing orders from the same store at the same moment. At one Washington, D.C. grocery store, the same dozen eggs appeared at five different price points simultaneously: $3.99, $4.28, $4.59, $4.69, and $4.79. McDonald Hopkins estimates that kind of variation could add up to roughly $1,200 a year for a family of four.

Facing pressure from Congress, the FTC, and the public, the platform abandoned the practice within weeks. But the episode accelerated a legislative wave already building. Maryland became the first state to act, with Gov. Wes Moore signing the Protection From Predatory Pricing Act on April 28, 2026. Food retailers with stores of at least 15,000 square feet, along with third-party delivery providers, are prohibited under the law from drawing on personal data to charge consumers higher individualized prices for food products. Violations carry fines of up to $10,000 each, rising to $25,000 for repeat offenders.

New Jersey followed on July 23, 2026, when Gov. Mikie Sherrill signed the Fair Price Protection Act, which prohibits any pricing strategy that varies the sale price of groceries based on personal data. Unlike Maryland's law, New Jersey's breaks new ground by giving consumers the right to sue — including through class action claims — under the state's Consumer Fraud Act. Across the country, Connecticut has put similar restrictions in place, and McDonald Hopkins reports that more than 50 surveillance pricing bills are now pending in 26 states.

At the federal level, the FTC released a surveillance pricing study in January 2025, confirming that a wide range of personal data — including geolocation, browser and purchase history, device type, battery life, and even mouse clicks — is already being used to set individualized prices. The agency issued orders to eight intermediary companies that use AI and personal information to help retailers set those prices. According to the study, retailers working with these intermediaries stood to see revenue climb by 2–5% and margins improve by 1–4% through personalized pricing.

A proposed enforcement policy statement released by the FTC on August 19, 2026, put businesses on notice that setting individualized prices using consumers' personal data without adequate disclosure could run afoul of Section 5 of the FTC Act. The agency has acknowledged it lacks authority to ban personalized pricing outright, but says it will enforce aggressively against deceptive or unfair practices. Under its framework, businesses that use personalized pricing must clearly disclose three things: that the price is personalized, the basis for that personalization, and the types of data used. McDonald Hopkins notes that catch-all language such as "prices may vary" will fall short of what the rule demands.

The legislative momentum reflects genuine public anxiety, but economists and marketing researchers say the backlash has outrun the evidence — and that some of the resulting laws may hurt the consumers they are meant to protect.

Some of the surveillance pricing laws are not only unlikely to protect consumers, they may even harm them.— Jean-Pierre Dubé, marketing professor, University of Chicago Booth School of Business

Part of the problem, according to CNN, is that the debate frequently blurs two distinct practices. Dynamic pricing — adjusting prices based on supply, demand, and other market conditions — has existed for decades. Happy hour, airline fares, and Uber surge pricing are familiar examples, and there is little evidence that dynamic pricing raises prices overall. A 2023 Harvard University study of a large restaurant chain found that an algorithm used to adjust food delivery prices smoothed out orders throughout the day by slashing prices during slow hours, bringing the average price down. A 2023 University of San Diego study found that dynamically pricing perishable goods cuts food waste by 21%.

Electronic shelf labels — digital price tags that can be updated remotely — have been swept into the same backlash, partly because unions fear the technology will eliminate the need for workers to manually change thousands of paper tags each week. CNN cited a study that analyzed more than 180 million price records at grocery stores and found "essentially no change in pricing behavior after these digital labels are installed."

A 2023 patent granted to Walmart for technology capable of pushing dynamic price changes remotely to electronic shelf tags set off a wave of public concern. The company assured customers that it does not price differently based on who a shopper is or what time of day it is. CNN spoke with Ioannis Stamatopoulos, a professor of operations at the University of Texas at Austin who studies dynamic pricing, and he argued that Walmart has little reason to walk away from its everyday-low-prices model. "They would rather keep you happy and coming back instead of risking your continued business for a few opportunistic cents," he said.

The data infrastructure powering true surveillance pricing — the kind that targets individuals rather than market conditions — is, however, enormous and growing. McDonald Hopkins puts the global data broker market at roughly $294 billion in 2025, with projections showing it climbing past $448 billion by 2031 at an annual growth rate of about 7.3%. Industry estimates suggest as many as 5,000 data brokers operate globally, with consumer data accounting for approximately 46% of the market. More than 250 companies are already deploying surveillance pricing tools.

The result is a regulatory landscape moving fast in multiple directions at once: state bans that may be too broad, federal disclosure rules that may be too narrow, and a commercial ecosystem that shows no sign of slowing. For businesses, the practical question is no longer whether to pay attention — it is how quickly the rules will change and in which direction.

Why it matters — Laws moving fast through dozens of state legislatures could reshape how every American is charged for groceries and other goods — but the same rules that block price gouging may also block discounts, and the line between the two is not yet clearly drawn.

Sources differ on Whether surveillance pricing raises prices overall: Senators Elizabeth Warren and Bernie Sanders blame surveillance pricing for driving up prices and warn AI will make things worse. (cnn.com) vs Economists, attorneys, and marketing experts say there is little evidence dynamic pricing raises prices overall; a study of 180M+ price records found no change after electronic shelf labels were installed. (cnn.com)

Reported by mcdonaldhopkins.com, cnn.com