S3612, the "Fair Price Protection Act," prohibits the use of personalized algorithmic pricing and surveillance pricing for groceries and other foodstuffs in New Jersey. The bill makes it an unlawful practice under the State’s consumer fraud law for a person to set or vary grocery prices based, in whole or in part, on personal data. It also bars the use of electronic shelving labels connected to technology that uses those pricing methods.
The bill defines key terms broadly, including "personal data," "location," "personalized algorithmic pricing," and "surveillance pricing," and it covers a wide range of grocery and household food-related items. It preserves certain pricing practices, including differences based on reasonable delivery or service costs, bona fide discounts that are clearly disclosed and uniformly available, and loyalty program discounts. If personal data is used to offer a permitted price difference, the bill limits that data’s use to that purpose only. The Attorney General is authorized to seek injunctions, compliance orders, damages, restitution, and other relief, and the Division of Consumer Affairs may adopt implementing regulations.
The bill would amend and supplement New Jersey’s consumer protection framework, specifically P.L.1960, c.39 (the Consumer Fraud Act), by creating a new unlawful practice tied to algorithmic and data-driven grocery pricing. It would affect grocery retailers, technology vendors, and any businesses using digital pricing systems or electronic shelf labels for food items, while leaving room for ordinary cost-based pricing and standard promotions.
The general sentiment reflected in the available legislative history is supportive: the Senate Commerce Committee reported the substitute bill unanimously, 4-0. No committee transcript is available here, so there is no recorded debate in the provided materials, but the committee action suggests broad agreement on the need to restrict data-driven pricing practices in grocery sales.
The main points of contention likely center on the scope of the ban and the breadth of the definitions, especially what counts as personal data, location data, and surveillance pricing. Potential concerns include whether the bill could limit legitimate dynamic pricing, loyalty programs, or technology used for operational efficiency, while supporters appear focused on preventing discriminatory or opaque pricing practices that could disadvantage consumers.
The bill would add a new consumer-protection prohibition to New Jersey law by making personalized algorithmic pricing and surveillance pricing for groceries and other foodstuffs an unlawful practice under the Consumer Fraud Act. It would also prohibit the use of electronic shelving labels tied to such pricing systems, authorize Attorney General enforcement, and allow the Division of Consumer Affairs to issue regulations. The measure would directly affect grocery retailers, food sellers, pricing software providers, and electronic shelf-label technology users, while preserving certain cost-based and clearly disclosed discount practices.
The available legislative record shows a favorable committee response, with the Senate Commerce Committee reporting the substitute bill 4-0. That unanimous vote suggests the bill had strong support at the committee stage. Because no transcript excerpts are provided, there is no detailed record of floor or committee debate, but the reported substitute indicates the sponsors and committee members were aligned on the need to address algorithmic grocery pricing.
The likely areas of contention are the bill’s broad definitions and its limits on modern pricing tools. Critics may question whether the ban could sweep in legitimate dynamic pricing, data-informed promotions, or operational uses of technology, especially given the inclusion of electronic shelf labels and the expansive definition of surveillance pricing. Supporters, by contrast, are likely focused on preventing price discrimination based on personal data, protecting consumer privacy, and ensuring that grocery prices are not manipulated through hidden or individualized algorithmic methods.