Personalized pricing lawsuits face uphill battle for class certification

With the rise of data-driven pricing technologies enabling online companies to potentially charge consumers individualized prices calibrated to their predicted willingness to pay, private plaintiffs are likely to initiate class litigation to redress perceived harms. But can personalized pricing claims survive class certification? Generally, class plaintiffs seeking damages must satisfy, inter alia, the predominance requirement to proceed as a class. While the existence of a common pricing algorithm deployed by the defendant may satisfy threshold requirements, the individualized nature of the alleged personalized pricing itself and the individual customer's personalized attributes poses formidable obstacles for establishing the predominance element required to certify a class under federal (and most state) law. While courts are just starting to grapple with these questions, what seems clear is that plaintiffs will likely face an uphill battle certifying a class alleging personalized pricing.

Personalized pricing defined

While merchants once posted uniform prices on shelves and in catalogues to all customers, advances in technology now enable online companies to offer specific prices to individual consumers. This practice, often called personalized pricing or surveillance pricing, draws on vast data reservoirs--browsing histories, purchase records, geolocation, device type, demographic proxies and inferred behavioral signals--to determine the maximum cost each buyer can tolerate. It can also be used to send personalized discounts to consumers (e.g., based on shopping history, or period of time since the consumer last logged in or shopped), or lure them back to the site.

Unlike other forms of price variation, personalized pricing operates at the level of the individual consumer, generally without that consumer's awareness. The mechanism is typically algorithmic: a machine-learning model, trained on historical transaction data and real-time behavioral inputs, generates a predicted reservation price for a given user and sets or adjusts the offered price or discount accordingly.

Legislative and enforcement interest

At present, no single federal statute comprehensively prohibits personalized pricing, and the federal government under the Trump administration has not signaled profound interest in regulating personalized pricing. That said, the FTC under the Biden administration took steps under its Section 5 and Section 6(b) authority to investigate surveillance pricing and the market for surveillance product technologies and products. And while the Robinson-Patman Act prohibits price discrimination between purchasers of commodities of like grade and quality where the effect may substantially lessen competition, its application to consumer-facing, algorithmic price discrimination is questionable as the scope of the statute is limited. 15 U.S.C. § 13.

Instead, state legislatures and their attorneys general have been dogged in their efforts to prevent, remediate and enforce use of personalized pricing in the online market, even where the use of this technology can ostensibly benefit the consumer with respect to a personalized discount or coupon, and thus result in a lower price paid. Indeed, the state attorneys general in California and New York have open investigations or inquiries into personalized pricing, with other AGs signaling similar concerns.

For the most part, personalized pricing is likely to run afoul of state consumer protection and privacy laws.

• State-level consumer-protection statutes potentially provide tractable causes of action. California's Consumers Legal Remedies Act and similar states statutes prohibit deceptive and unfair trade practices and, importantly, many of these statutes extend a private right of action, opening the door for state class actions. Cal. Civ. Code §§ 1770 et seq. State price-discrimination statutes, such as California Business & Professions Code § 17045, which prohibits certain secret rebates and unearned discounts, may add another layer. In late 2025, New York signed into law the FAIR Business Practice Act, which expanded the state's UDAP and unfair competition law, and now requires the explicit disclosure of certain algorithmic pricing.

• Privacy law may be a parallel track. The California Consumer Privacy Act (Cal. Civ. Code §§ 1798.100 et seq.) and the California Privacy Rights Act create rights to know about and opt out of the sale of personal information, which plaintiffs may argue encompasses the data-brokering that enables personalized pricing. Indeed, the California Attorney General's recent enforcement sweep is predicated on personalized pricing violating data privacy and processing law.

Some states are taking an even more aggressive and focused approach to personalized pricing. For example, New Jersey Senate Bills 3612 and 3732, introduced in February 2026, would prohibit businesses from using consumers' personal data to set prices for merchandise or services. See also Illinois SB 2255.

With this influx of attention, it seems just a matter of time before private plaintiffs seek redress on a class-wide basis. But can they succeed in getting class treatment for something that is so inherently personal?

Class certification framework

As plaintiffs increasingly file putative class actions challenging personalized pricing practices, courts must determine whether the class device is a suitable instrument for resolving these disputes--or whether the individualized nature of the claims defeats certification.

Federal Rule of Civil Procedure (Rule) 23 establishes the requirements for class certification. A plaintiff must satisfy all four elements of Rule 23(a)--numerosity, commonality, typicality and adequacy of representation--and must additionally demonstrate that the action falls within one of the Rule 23(b) categories. Wal-Mart Stores, Inc. v. Dukes, 564 U.S. 338, 345 (2011). For damages classes, plaintiffs must also show that common questions of law or fact "predominate over any questions affecting only individual members" and that the class format is "superior" to other available methods for fairly and efficiently adjudicating the controversy. Fed. R. Civ. P. 23(b)(3). Some circuits also recognize an independent ascertainability element, requiring that class members be identifiable through objective criteria. Byrd v. Aaron's Inc., 784 F.3d 154, 163 (3d Cir. 2015). Rule 23 is not a "mere pleading standard," and courts must conduct a "rigorous analysis" to determine whether the prerequisites are satisfied, even if that analysis overlaps with the merits. Comcast Corp. v. Behrend, 569 U.S. 27, 33 (2013).

The predominance requirement of Rule 23(b)(3) is a consequential hurdle and "far more demanding" than commonality under Rule 23(a)(2). Amchem Products, Inc. v. Windsor, 521 U.S. 591, 623-24 (1997). Where individualized issues--particularly regarding injury and damages--predominate, certification is typically denied. Comcast, 569 U.S. at 35-38. For that reason, the Supreme Court reversed class certification in Comcast because there the plaintiff's damages model required individual-by-individual calculations, thus defeating predominance. Id. at 34 ("Without presenting another methodology, respondents cannot show Rule 23(b)(3) predominance: Questions of individual damage calculation will inevitably overwhelm questions common to the class.").

The predominance battleground

Plaintiffs and defendants will take different approaches to the predominance element, with the former arguing it is surely met by virtue of the common algorithm itself, while the latter will argue that the very nature of personalization defeats any notion of predominance across the class.

Plaintiffs will contend that the predominance element is met because the defendant's pricing algorithm is the common evidence capable of resolving liability on a class-wide basis. They will likely argue that the defendant's pricing algorithm is a sufficient "common policy" to satisfy predominance. The theory there would be that because every class member's price was generated by the same model, under the same firm-wide policy, the question of whether that model was unlawful could be resolved in a single proceeding without examining each individual transaction. Plaintiffs will likely analogize to price-fixing cases, where some courts have certified classes under the theory that a common scheme to fix prices constitutes the central, predominating issue, even though individual damages will necessarily vary. See, e.g., In re Capacitors Antitrust Litig., No. 14-cv-03264-JD, 2018 WL 5980139, at *4-10 (N.D. Cal. 2015) (certifying class where plaintiffs demonstrated common impact through expert analysis of overcharge attributable to cartel conduct).

For their part, defendants will almost certainly argue that the personalized pricing claim, by its own terms, will require individualized evidence as to both liability and damages. Defendants will counter that liability and damages hinge on individualized determinations and thus individualized issues will predominate. Where the alleged deception consists of concealing the existence of personalized pricing, defendants will argue that any deception, plaintiffs' subsequent reliance, and any resulting damages are quintessentially individual questions. See McLaughlin v. Am. Tobacco Co., 522 F.3d 215, 25 (2d Cir. 2008) (partially abrogated on other grounds by Bridge v. Phoenix Bond & Indem. Co., 553 U.S. 639 (2008)) ("[R]eliance is too individualized to admit of common proof."). Also In re Rail Freight Fuel Surcharge Antitrust Litig., 934 F.3d 619, 626 (D.C. Cir. 2019) ("Given the need in this case for at least 2,037 individual determinations of injury and causation, the district court did not abuse its discretion in denying class certification on the ground that common issues do not predominate.").

Conclusion

The fundamental tension in personalized pricing cases is architectural and existential to the alleged legal violation itself. Personalized pricing operates through individual differentiation--each consumer receives a distinct price precisely because the system has modeled that consumer as a distinct economic actor. The individualization that plaintiffs claim is unlawful is precisely the feature that makes class-wide adjudication doctrinally strained; the same algorithm that creates the common question also generates the individualized answers. Plaintiffs are sure to argue that it would be manifestly unfair to allow personalized pricing to evade class treatment for this reason alone, while defendants will argue that individual actions are better suited to resolve individual claims and matters of proof. Where the courts land on these emergent and novel issues remains to be seen.