FTC Probes Hidden Personalized Pricing Models

The Federal Trade Commission (FTC) has found that personalized pricing is a standard operating model for a significant portion of the online retail economy. This conclusion stems from an ongoing 6(b) surveillance pricing study initiated in July 2024 and expanded with initial findings published in January 2025.

Orders were issued to eight non-retail companies, including Mastercard, Revionics, and Accenture. These firms are described as middlemen, providing the pricing optimization software and consulting services that enable retailers to set individualized prices. They were chosen for advertising their use of AI and other technologies to target prices for individual consumers.

The FTC's January 2025 findings detailed various consumer signals used to determine these prices. These include location, browsing and purchase history, device information, and credit background, with some systems also incorporating demographic inferences and third-party data.

In August 2026, the FTC advanced a proposed enforcement policy statement. This proposal would mandate that retailers disclose when a price has been personalized. While not banning the practice, the FTC frames this disclosure as a minimum consumer protection, ensuring awareness that prices are individually calculated.

Industry groups have contested the FTC's terminology, arguing it overstates current practices. This proposal serves as an enforcement signal for how the FTC intends to interpret existing consumer protection laws regarding pricing personalization.

Tools like VPNs can mitigate some pricing signals, such as IP-based location, by routing traffic through different servers. However, they do not change prices tied to user accounts or logged-in purchase history. Basic privacy measures like browsing in private windows or without logged-in accounts also limit the data available to pricing engines.