State Data-Driven Pricing Bans Would Backfire on Consumers

State lawmakers across the United States are taking aim at the practice of using personal data to algorithmically tailor prices to different consumers. Unfortunately, their proposed state bills conflate data-driven pricing with harmful practices such as discriminatory or deceptive pricing. That misunderstanding threatens to raise prices and limit consumer choice in competitive markets.

California and New York are at the forefront of these legislative efforts. A proposed California bill, for instance, seeks to prohibit "surveillance pricing," or offering a non-standard price to a specific consumer or group based on covered data. And New York already requires businesses to disclose to consumers if they are using algorithmic pricing.

Policymakers are concerned that companies are leveraging sensitive personal data—such as their location or browsing history—to create potentially unfair or discriminatory prices. However, a blanket ban on data-driven pricing fails to recognize that such practices can, in fact, lead to more inclusive markets and offer significant advantages for consumers, especially those with lower incomes.

Some critics argue it is unfair to charge different consumers different prices. But uniform pricing often locks out lower-income buyers. Tailoring prices can broaden access, especially when used to offer discounts or incentives. For example, online retailers can offer targeted promotions to new or lapsed customers based on data signals like whether someone has made a purchase in recent months. Under proposed state bills that either ban or require public disclosure of any personalized pricing tied to consumer data, companies may stop offering these deals entirely for fear of enforcement or reputational blowback. The result would be fewer discounts, more uniform pricing, and higher consumer costs.

Critics of algorithmic pricing also fundamentally misunderstand the role of data in modern commerce. For digital retailers, travel platforms, grocery delivery services, and other consumer-facing businesses, using customer data to make pricing, stocking, or marketing decisions is central to how they function, and algorithmic pricing is not inherently harmful to consumers.

Rather than creating a patchwork of state laws that do real harm to consumers, policymakers should adopt a three-part strategy.

First and most importantly, regulators should protect consumers from harm by rigorously enforcing existing consumer protection, anti-discrimination, and deceptive practice laws, which apply to data-driven practices just as they do to traditional business practices. Second, Congress should empower consumers and prevent future harms by passing a comprehensive federal privacy law that gives people clear rights over their personal data and preempts confusing and fragmented state-level rules. Third, the FTC should make responsible innovation easier by issuing clear guidance that distinguishes between fair personalization, like targeted discounts, and unfair and deceptive pricing practices.

The path forward on data-driven pricing requires nuance, not broad prohibitions. State lawmakers' efforts to protect consumers from data-driven pricing risk eliminating the very discounts and targeted offers that make products more accessible to price-sensitive consumers. The stakes are too high—and the potential benefits too significant—to let misunderstanding drive policy that ultimately leaves consumers worse off.