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The US consumer protection agency FTC is investigating whether nine companies use personal data to calculate prices or compensation individually. On 29 October 2026, it requested information from Delta, United, JetBlue, Lyft, Uber, DoorDash, Instacart, Target and Walmart. The step is a market study and not evidence of unlawful conduct. For marketing teams, one question now takes center stage: when is a dynamic price ordinary demand management – and when is it a barely recognizable, data-based individual decision?
Nine companies, two types of algorithms
The FTC announcement of 29 October addresses two separate issues. On the one hand, the agency wants to know whether prices for flights, rides, deliveries and goods vary according to customer characteristics. On the other hand, it is examining whether platforms adjust the compensation of drivers and delivery workers based on personal behavioral data.
The companies are to disclose the data, procedures and tools they use; the response deadline is 45 days from receipt of the respective order. The inquiry is conducted under Section 6(b) of the FTC Act and serves to investigate the market, not directly to initiate enforcement proceedings.
Three pricing logics marketers need to tell apart
Dynamic prices react, for example, to demand, time of day, capacity or inventory. Personalized prices, by contrast, incorporate data about individual people or devices, such as purchase history, location or presumed willingness to pay. Personalized discounts can use the same data signals but are not equivalent to an individual price increase. Legal consequences depend on the specific model and the market.
In August 2026, the FTC published a draft on enforcement for personalized pricing: opaque individual prices could be misleading. The paper is not a general prohibition standard. In parallel, since November 2025, New York has required an explicit disclosure for algorithmic prices based on personal data.
An even further-reaching One Fair Price Act, which would ban certain forms of “surveillance pricing”, was still not in force according to a legal assessment updated on 27 October . Passed legislation and applicable law must not be confused here.
What already applies in Germany and the EU
For German retailers, this is not a new American obligation that is automatically adopted. However, the EU consumer information on personalized prices explains an existing requirement: consumers must be informed before an online contract if a price was personalized on the basis of automated decision-making. In addition, data protection and unfair competition law remain relevant; a mere notice does not make every data processing activity permissible.
For campaigns with individualized vouchers, retargeting or loyalty segments, it should therefore be documented which data actually influences the final price. How AI-supported product search is assessed in Germany is shown in our analysis of the KPMG/EHI study on AI shopping.
Concrete review questions for commerce and media teams
A solid audit separates the pricing rule, the data source and the advertising message: Is a difference justified by general availability or by an individual profile? Is the price already promised in an ad or only calculated at checkout? Can differences between app, web and brick-and-mortar retail be explained, and are notices displayed in the right place?
The interface between customer data and advertising is growing: Target is developing additional retail media touchpoints, while the FTC case Publicis/LiveRamp shows how authorities are examining data access and data protection in the adtech market. What matters is not the mere existence of an algorithm, but the concrete use of personal data – and whether consumers can recognize it.