Podcast - Surveillance Pricing vs. Dynamic Pricing: What Companies Need to Know

Anthony DiResta: Welcome to another podcast of Clearly Conspicuous. As we noted in previous sessions, our goal in these podcasts is to make you succeed in this current regulatory and governmental environment that's actually very aggressive and progressive. We want to make you aware of what's going on with the federal and state consumer protection agencies and give you practical tips for success. It's a privilege to be with you today.

Today we discuss surveillance and dynamic pricing. So we're diving into one of the hottest topics at the intersection of technology, privacy and consumer protection: surveillance pricing and dynamic pricing. Five states have now enacted surveillance pricing laws, Congress held hearings just last week, and state attorneys general are launching enforcement sweeps. If you're a general counsel or compliance officer at a retailer, airline, delivery platform or food company, you need to be paying attention. Joining me today is my colleague Benjamin Genn from Holland & Knight's Consumer Protection Defense and Compliance Team, who recently presented on this at a major conference. Ben, welcome. It's great to be with you.

Benjamin Genn: Thanks, Tony. Great to be here. This is a topic that's evolving almost weekly, so I'm glad we can break it down for our listeners.

Anthony DiResta: Great, thanks, Ben. Well, let's start with the basics. What's the difference between dynamic pricing and surveillance pricing, and why does that distinction even matter legally?

Benjamin Genn: That's a great question, Tony. So dynamic pricing is adjusting prices based on supply, demand, time of day or market conditions, and this has existed for decades. Think about airlines, hotels and ride-sharing apps who frequently do this. In food retail, think surge delivery pricing or end-of-day markdowns. Dynamic pricing uses aggregate market signals, not personal data, and it's generally considered lawful. But surveillance pricing is different. It uses personal data, such as browsing history, location, demographics, income, purchase history and even device type to set individualized prices. In other words, prices vary by who the consumer is, and not aggregate market conditions. Understanding this distinction is itself a defense, because companies that can document they're doing lawful dynamic pricing rather than surveillance pricing are in a much stronger position. And one thing that's clear is that regulation is here, and it's not theoretical. As you mentioned Tony, fvour states have enacted bans – Maryland, Connecticut, Vermont and New Jersey – and we're tracking over 40 bills in 24-plus states.

Anthony DiResta: Ben, this is fascinating. Why is there so much political energy around this issue right now?

Benjamin Genn: There's several factors that are converging here. And the first is consumer trust. When people learn that prices might vary based on who they are, it undermines the basic assumption of fair dealing. So the price on the shelf should be the price everyone pays. The second part is the phrase "willingness to pay" has become a red flag for regulators. Optimizing prices based on what each consumer will tolerate feels like extraction, not competition. Third, we're talking about groceries and food. These are necessities and not discretionary purchases. Surveillance pricing on necessities feels like exploitation of captive consumers. And fourth, after years of inflation, consumers are hypersensitive to any perception that companies are using data to squeeze more out of them. And the political environment is primed for this issue, which is why we're seeing action from Congress, the FTC and state AGs simultaneously.

Anthony DiResta: Thanks, Ben. Well, tell us about the federal enforcement picture. What is the FTC doing, and has the change in administration made a difference?

Benjamin Genn: Tony, the FTC has been active regardless of party. Under Chairman Ferguson, the FTC scaled back broad rulemaking, but ramped up targeted enforcement. There's a $60 million settlement with a grocery delivery platform, a $25 million settlement with a food delivery app and the DOJ's settlement with a rental housing software provider restricting algorithmic data sharing. The FTC's advanced notice of proposed rulemaking (ANPRM) from April 2026 explicitly covers personalized pricing disclosure. I think the key takeaway here, Tony, is that junk fees and surveillance pricing enforcement are converging, so companies need to track both of these issues together.

Anthony DiResta: Fascinating, Ben, thank you. In Congress, was it just last week the Senate Judiciary Committee held a hearing on surveillance pricing? What happened, and why does that matter? What does it signal?

Benjamin Genn: You're right. This was a significant escalation. Senator Josh Hawley's subcommittee held a hearing titled "Your Data, Their Profit: The Consumer Cost of AI Surveillance Pricing." Senator Hawley described AI-driven surveillance pricing as the "unholy trinity of everything America hates." He cited a major grocery retailer's $500 million in revenue from selling consumer data, and witnesses testified about a 230 percent fare increase for funeral travel on a major airline. Hawley mentioned that he expects to introduce his own legislation soon, which has not happened yet.

And just this past week, the House Energy and Commerce Committee's ranking member sent letters to eight major airlines requesting answers by August 25 about their use of consumer data in pricing. The letter identifies the data categories Congress is scrutinizing, such as identity, age, race, income, spending patterns, loyalty programs, browsing behavior, location and device characteristics. So congressional scrutiny has expanded from grocery and retail into aviation. Companies should assume that they will need to explain their pricing data inputs and methodology to Congress.

Anthony DiResta: Ben, as I understand it, DOJ has gotten involved, and they have also been signaling something to companies. Am I correct?

Benjamin Genn: Yes. In June 2026, DOJ signaled that criminal enforcement of algorithmic pricing collusion remains on the table, not just civil penalties. Companies sharing pricing data through common algorithmic platforms face potential criminal liability. And this, as you can imagine, Tony, dramatically raises the stakes.

Anthony DiResta: Ben, it sure does. What about enforcement at the state level? Should companies be more focused on state AGs than the FTC right now?

Benjamin Genn: Tony, near-term risk from state AGs may exceed federal enforcement risk since AGs can move first using existing UDAP (unfair or deceptive acts or practices) authority. They do not need any new surveillance pricing statute, per se. Keep in mind that the New York state AG already demanded answers from a grocery delivery platform after a consumer advocacy organization found 23 percent price differences between consumers, and that platform ended those tests. The California AG launched a surveillance pricing sweep, and a 16-state AG coalition urged the FTC to issue a surveillance pricing rule. One thing to bear in mind is that attorneys general findings often become the factual record for any follow-on private actions.

Anthony DiResta: Ben, let's talk about New Jersey. I think they have a new law specifically. What does it do, and what should companies know about it?

Benjamin Genn: New Jersey's Fair Price Protection Act prohibits using personal data, such as online activity, location, purchasing history, inferred income and biometric data, to charge different prices for identical grocery products. Penalties are up to $50,000 per violation with treble damages and a private right of action. Notably, Tony, it also includes a one-year electronic shelf label moratorium. And if I may touch on Connecticut's law, which takes effect next July 2027, that requires a disclosure label along the lines of "This Price Was Increased Using Your Personal Data." New York's One Fair Price Act awaits the governor's signature, and if signed, it will replace the disclosure-only requirements with an outright ban.

Anthony DiResta: Well Ben, what about loyalty programs? Are those caught up in these laws?

Benjamin Genn: Yes. This is one of the most important compliance questions. Most state laws carve out traditional loyalty programs and bona fide group discounts. New Jersey's law explicitly does not ban loyalty programs. But the key distinction is between offering a discount to loyalty members versus using loyalty data to set individualized prices. A loyalty program that gives all members the same discount is generally safe. But if you're using loyalty program data such as purchase history, browsing behavior and inferred income to charge different loyalty members different prices for the same product, that crosses the line. Loyalty programs are both the primary source of the data creating exposure and potentially a safe harbor if structured correctly. So companies should audit how loyalty data flows into their pricing algorithms, under privilege with counsel, to understand which side of the line their programs fall on.

Anthony DiResta: Ben, I have to ask this, have there been any pushbacks? Any state where legislation has failed?

Benjamin Genn: Yes. Colorado's governor vetoed a surveillance pricing bill in early June of this year, saying it was too broad and could punish "differentially lower prices, not just higher prices." Even in Democratic-leaning states, overly broad bills can fail, but the direction of travel is clear here, Tony.

Anthony DiResta: Well, you mentioned earlier electronic shelf labels. There seems to be a lot of political energy around that. What's the reality?

Benjamin Genn: Electronic shelf labels (ESLs) are a political flashpoint even though they're legitimate technology. ESLs can cut food waste, and a large percentage of price changes occur between 2 and 5 a.m. But there are 28 bills in 16 states that we're tracking so far that target ESLs, and a majority of voters think ESLs will raise prices. An even larger majority of Americans support banning surveillance pricing, so legislation is inevitable. It's just a question of how restrictive.

Anthony DiResta: Fascinating, Ben. What about antitrust risk and the private litigation landscape?

Benjamin Genn: What's become more clear over the past several years, Tony, is that the Robinson-Patman Act is back with bipartisan support. The FTC brought its first RPA suits in a generation against a major beverage distributor and a major food and beverage company, targeting pricing disparities that harm small grocers. On artificial intelligence risk, shared algorithmic pricing tools can create tacit collusion, which is the rental housing software model we mentioned earlier. A key point here is that outsourcing your pricing to a third-party vendor does not eliminate your liability. And I want to flag that the private plaintiffs' bar is also activating. Interestingly, they're pressing wiretapping and session replay theories and merging those with surveillance pricing claims. Tony, my final point here is that, as we mentioned earlier, state AGs' findings can often become the factual record that class action lawyers cite, so it's really a one-two punch of regulatory exposure followed by private litigation.

Anthony DiResta: Ben, I have to ask this, can you give me a real-world example of how companies should respond to this scrutiny?

Benjamin Genn: Sure. One major airline's response is instructive. When that airline announced plans to increase AI use for flight pricing, three senators wrote demanding answers. The airline responded by clarifying that they do not use AI for individualized pricing based on personal data, only for aggregate dynamic pricing. Critically, the airline's response worked because they had documentation ready. They could point to specific policies showing their AI uses aggregate demand signals and not personal data. So that's really the model, Tony. Document your methodology before the inquiry arrives, not after. The dynamic-versus-surveillance distinction is your best defense, but companies need to explain their methodology clearly and immediately when scrutiny comes.

Anthony DiResta: Well, what if a company believes they're only doing lawful dynamic pricing, should they still be concerned?

Benjamin Genn: That's exactly the companies that need to audit their pricing models. The line between aggregate market signals and personal data inputs isn't always obvious, especially when loyalty program data, location or device type flows into pricing algorithms through third-party vendors. Many companies are genuinely surprised by what their own systems are doing. So don't assume you're in the clear. Audit first, and then you'll know.

Anthony DiResta: Well, Ben, moving on, what typically triggers a regulatory inquiry into this space?

Benjamin Genn: Tony, I think three things put companies on regulators' radar: consumer complaints about price discrepancies, media coverage of algorithmic pricing experiments and using the same third-party pricing vendor as competitors already under investigation. If you've received a congressional inquiry letter, expect state attorneys general to follow. These investigations tend to cascade.

Anthony DiResta: Ben, thinking about a focus here, which industry should be most concerned, and what should they be doing now?

Benjamin Genn: Tony, as is clear from the congressional inquiries of late, the highest-risk industries are aviation, grocery stores, big-box retailers, food and grocery delivery apps, hotel operators and multifamily rental housing. As you can see, that's quite a broad spectrum of the economy. If you're a general counsel in these sectors, this should be at the top of your risk register. And to put the penalty exposure in perspective: New Jersey allows up to $50,000 per violation with treble damages. Connecticut and New York have their own penalty structures, so each consumer transaction could be considered a separate violation. As you can imagine, for a national retailer, the math gets serious very quickly. So the time to build compliance infrastructure is now, because proactive compliance is far less costly than reacting after enforcement begins.

Tony, here's what companies should do. Audit pricing algorithms across all their channels. Evaluate vendor contracts for shared liability risk. Audit loyalty program data practices under privilege. Implement transparency measures where required. Train their teams on the legal distinction between lawful dynamic pricing and surveillance pricing. Document legitimate business justifications for every pricing differential and prepare an incident response plan for when, not if, a regulatory inquiry arrives. Of course, they can always contact our consumer protection team directly. We're helping companies across these high-risk industries build compliance programs, respond to regulatory inquiries and prepare for what's coming. The earlier you engage, the better position you'll be [in].

Anthony DiResta: Ben, that was just terrific, both in terms of content and the timing is ideal. So, ladies and gentlemen, if you're in food retail, grocery, aviation, delivery or hospitality, the time to act is now. Audit your pricing practices, understand your data flows and build your compliance infrastructure before a regulator comes calling or knocking at the door.

So please stay tuned for further programs as we identify and address the key issues and developments and provide strategies for success. Folks, I wish you continued success and a meaningful day. Thank you.