Surveillance Pricing: Exploiting Information Asymmetries

Before the 1870s, retail goods rarely carried fixed prices. Instead, haggling was the norm. Customers and store clerks engaged in a song and dance, testing the other’s economic limits. Then, on the eve of the Philadelphia World’s Fair, businessman John Wanamaker transformed an abandoned railroad station into the Grand Depot, one of the first department stores in the United States. At the grand opening, each item in the sprawling store was affixed with a conspicuous label declaring a non-negotiable price. When millions came to the city for the fair, many had their first encounter with fixed price tags. The elimination of haggling saved both customers and clerks time, making the market significantly more efficient. Fair visitors brought the idea of the price tag home with them. Soon, businesses around the world adopted fixed prices and price transparency.

One hundred and fifty years later, the datafication of the economy is causing the retail experience to regress to a form of variable pricing far more coercive than the haggling of the past. With online shopping, social media, and data collection, modern corporations have access to more information than ever before. Retailers can view your purchase history, location, personal demographics, and much more. This has enabled businesses across a variety of sectors to engage in surveillance pricing—the practice of extracting and exploiting personal information in order to charge customers different prices for the same product or service. Today, variable pricing is back, but this time the seller knows everything about you.

The viability of surveillance pricing—its profitability, ubiquity, and exploitative nature—hinges on the presence of market failures. Severe information asymmetries are perhaps the most insidious. While corporations have access to data brokers, online behavioral advertising, and algorithms that can adjust prices in real time, consumers are more disempowered than ever.

A Tradition of Consumer Exploitation

Surveillance pricing is not new. American capitalism has a long tradition of consumer exploitation, including targeted advertising, behavioral advertising, price discrimination, and algorithmic pricing. All of these tactics make it easier for corporations to extract more consumer surplus; that is, to close the gap between what consumers are willing to pay and what they actually pay.

Since the 2010s, companies have been experimenting with more precise and invasive pricing schemes. In 2011, Ticketmaster rolled out “dynamic pricing,” which adjusted ticket prices based on demand and caused prices to reach levels that captured virtually all consumer surplus. Later that year, Uber implemented its notorious “surge pricing,” which applied multipliers to the price of a ride during weekends, special events, and inclement weather. In 2012, Orbitz infamously displayed more expensive hotel offers to Mac users on the assumption that they were less price-sensitive. A 2015 ProPublica investigation revealed that Princeton Review charged higher prices to customers from ZIP codes with more Asian people. Staples and Target have both experimented with GPS-based pricing, charging higher prices to customers close to them and far from competitors. In 2025, a group of nonprofits revealed that some grocery prices on Instacart differed by as much as 23 percent from one customer to another.

These pricing strategies share a common characteristic: using information asymmetries to take advantage of consumers when they are most constrained and captive. Crucially, the objective of surveillance pricing is not personalization, but maximum extraction.

Beyond Laws Mandating Disclosure

While an outright ban on surveillance pricing offers a direct solution, such an approach still leaves underlying systemic problems unaddressed. The extractive aspects of a failing oligopolistic market—data brokers, online behavioral advertising, information asymmetry, and consumer isolation—remain even if corporations can no longer openly engage in surveillance pricing. Conversely, mere disclosure—which typically only requires companies to inform consumers that prices may be set based on personal data—is far too narrow to meaningfully protect consumers from price gouging. Disclosure regimes outsource accountability by placing the onus on consumers to determine how their data may affect the price they are shown instead of changing corporations’ practices. Laws mandating disclosure may leave consumers more informed, but they fail to lower prices and prevent companies from amassing personal data.

In May 2025, New York became the first state to pass a law specifically targeting surveillance pricing. The Algorithmic Pricing Disclosure Act requires companies that set prices using an algorithm based on consumers’ personal data to display a disclosure stating, “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” The Act defines personal data as “any data that identifies or could reasonably be linked, directly or indirectly, with a specific consumer or device.” Several other states have pending bills that would either ban surveillance pricing outright or require similar disclosures.

Although New York’s Algorithmic Pricing Disclosure Act represents a step in the right direction, it ultimately falls into the transparency trap. That is, transparency alone will not curb the harms of surveillance pricing. The New York law merely mandates that businesses acknowledge their use of surveillance pricing. The consumer is left informed but unprotected. Without options to safeguard their data, the value of the disclosure is questionable at best. Furthermore, individuals often lack the necessary expertise or resources to make sense of disclosed information, resulting in information overload or fatigue. The disclosure approach is untenable as digital products and services become increasingly essential for navigating daily life.

Addressing surveillance pricing requires more than mere transparency; it necessitates meaningful accountability. To that end, recent federal bills offer a more impactful solution by including a missing ingredient: enforcement. The Stop AI Price Gouging and Wage Fixing Act of 2025 would eliminate surveillance pricing and wage setting. With respect to surveillance pricing, the proposed bill defines “surveillance data” as not only data obtained by the business implementing surveillance pricing but information gathered or purchased from other sources. Crucially, state attorneys general and private citizens could bring civil actions for alleged violations. Additionally, the Act empowers the FTC to impose fines and consumer redress on offenders.

While federal legislation faces significant hurdles in a divided Congress, there is an appetite for regulating surveillance pricing. The outlook is more positive in state legislatures, where lawmakers are more sensitive to constituents’ concerns about the rising costs of groceries and housing. Despite the lack of bite in some laws, business interests were quick to call them too broad. In July 2025, the National Retail Federation challenged the New York disclosure law on First Amendment grounds, arguing that the Act compels members to publish misleading opinions.