FTC Moves Against Personalized Pricing as Studies Find Wide Gaps in Online Costs
The Federal Trade Commission has proposed an enforcement policy statement on personalized pricing, warning that companies failing to disclose how personal data shapes prices could violate federal consumer protection law. The action follows investigations showing significant price differences for groceries and rideshare trips.
The Federal Trade Commission has proposed a new enforcement policy statement aimed at personalized pricing, signaling that companies failing to clearly tell consumers how their personal data affects the prices they see could violate federal consumer protection law. The proposal, published on Aug. 19, 2026, stops short of banning the practice outright, but it puts retailers and the data intermediaries behind them on notice that the agency is watching how consumer information is used to set prices, discounts and product rankings.
Personalized pricing differs from the dynamic pricing that most shoppers already know. Dynamic pricing adjusts costs based on broad market conditions such as supply, demand, inventory, time or location. Rideshare fares rise when many people need cars at once, and airline tickets and hotel rooms shift as availability changes. Personalized pricing goes further, using information about a specific consumer to determine the price or offer that person receives. Two people looking for the same product could see different offers because of data connected to them.
A related practice, known as price steering, leaves the actual prices alone while changing the order of products shown to a shopper. FTC research found that pricing tools can use consumer data to give certain products more prominent placement, including potentially showing higher-priced items first. The agency says consumers generally expect prices to move with supply and demand, but a price influenced by browsing habits, buying history or other personal information can come as a surprise.
The FTC's examination of surveillance pricing found that third-party pricing companies can use detailed information when helping retailers tailor prices, promotions or product rankings. The intermediaries it reviewed worked with at least 250 clients selling goods and services ranging from groceries to clothing. Companies can combine first-party information with data from outside sources, including loyalty programs, reservation systems, e-commerce platforms and data brokers. That does not prove every client charges individualized prices, but it shows the technology exists to combine detailed consumer information and use it to influence prices, discounts and which products shoppers see.
Recent investigations have added concrete examples. In June 2026, Consumer Reports published results from a months-long study of Uber and Lyft pricing that used 174 volunteers to check more than 40 routes across the United States. For the 30 virtual routes in its analysis, the study found a median gap of 42.4% between the lowest and highest price groups. On some routes, people checking the same trip within minutes of one another received several different prices. The study was designed to reduce the effects of time-based pricing by having volunteers check routes at roughly the same time, but it could not control for every factor inside the companies' pricing systems, including driver supply, estimated arrival times, traffic, routing differences and network delays. Uber and Lyft disputed the conclusions, saying they do not use personal data to personalize base fares and do not engage in behavioral or surveillance pricing. The study shows riders can receive significantly different prices for similar trips checked around the same time, but it does not prove those differences were caused by personal data.
Online groceries have produced another striking example. In December 2025, Consumer Reports, Groundwork Collaborative and More Perfect Union reported that nearly three-quarters of the grocery items they tested on Instacart were offered at different prices to different shoppers. The investigation involved 437 shoppers across four U.S. cities. Some items showed differences of as much as 23% between the lowest and highest prices, and totals for identical baskets varied by an average of about 7%. Using an Instacart figure for how much a household of four spends on groceries, the researchers estimated that a similar difference over a year could amount to roughly $1,200. Instacart strongly disputed that annual extrapolation, saying the limited tests should not be treated as though a household would continually pay higher prices throughout an entire year. The company also said the pricing tests were randomized and did not use personal information.
The FTC's proposed policy statement does not resolve the debate over how widespread personalized pricing has become, but it establishes a clear expectation: companies that use personal data to shape what consumers pay must be transparent about it. For shoppers, the practical takeaway is that the price on a screen may reflect more than supply and demand. The agency's action signals that Washington is now paying close attention to the algorithms and data streams that sit behind everyday online purchases.
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