The FTC's Personalized Pricing Proposal: What It Means for Negotiated Pricing

The Signal We Flagged Got Louder

When we wrote about coupon fatigue earlier this year, we mentioned in passing that the FTC had proposed an enforcement policy statement on personalized pricing. That was a one-paragraph aside at the time. It has turned into something merchants should actually read, because the definitions in it are wider than the headlines suggest.

This post is the deep dive on that proposal: what it actually says, why a trade association thinks it reaches ordinary promo tactics, and where a "make an offer" flow sits relative to all of it. None of this is legal advice — it's a merchant's reading of a public document, and the document isn't even final yet.

What the FTC Actually Proposed

On August 19, 2026, the FTC announced a proposed "Enforcement Policy Statement Regarding Personalized Pricing" and opened it for public comment under Docket No. FTC-2026-1057. The Commission vote to publish it was 2-0.

The FTC defines personalized pricing as "the use of personal data to set prices according to the amount that a company believes an individual consumer is willing to spend." Chairman Andrew Ferguson framed the concern in terms of what a shopper expects when they look at a price tag:

"When consumers see a listed price, they expect it to be same price that everyone else sees, not the retailer's estimate of how much they are willing to pay based on their personal data. The FTC does not have the legal authority to ban personalized pricing in all circumstances, but businesses that fail to tell consumers how their personal data is being used to set a price may be in violation of the FTC Act and other laws we enforce. We are seeking public input on this draft statement, which would put businesses engaged in or considering personalized pricing on notice that the Trump-Vance FTC will not hesitate to enforce the law in this space."

It's Not a Ban, and It's Not a Rule

This part gets lost in coverage. The proposed statement itself says plainly that Congress has not given the FTC authority to prohibit personalized pricing outright. What's on the table is enforcement policy under Section 5 of the FTC Act — the unfair-or-deceptive-practices authority — not a new rule and not a prohibition.

The trigger is disclosure. Where consumers reasonably expect a price is the same for everyone, the statement says a business must clearly and conspicuously disclose three things: that the price is personalized, the basis for the personalization, and the types of data used. Failing to disclose those is, in the FTC's words, "likely to constitute an unfair or deceptive act or practice."

The document also singles out discounts that aren't what they appear to be. Consumers who "reasonably believe that a personalized price is a discount based on their purchase history with that retailer when it is in fact a higher price based on information about their disposable income or their shopping habits with other firms... may be deceived." And telling a shopper only that they've been "specially selected" for a price would likely be misleading, because it leaves out the information the statement says you owe them.

The comment window was extended by seven days on September 3, moving the deadline from September 18 to September 25, 2026. As of today that's 10 days out, so anything in this post could shift before the statement is finalized.

Why This Is Bigger Than "Surveillance Pricing"

Most coverage framed this as a crackdown on retailers quietly charging you more because your phone battery is low. Fair enough. But the Ecommerce Innovation Alliance, a trade association, published an analysis on August 27 arguing the definitions sweep in tactics most DTC stores run every week.

Their core point is that the statement's "definitions and legal theories are not limited to price increases... they are broad enough to raise serious questions about everyday retention and promotional practices, including targeted discounts, abandoned-cart offers, loyalty pricing, and geofenced promotions."

The mechanism, as EIA reads it, is that the trigger is consumer expectation, not price direction. The theory turns on whether a price "varies based on personal data" in a context where consumers expect uniform pricing — and, they note, "nothing in the deception framework is limited to prices that go up." EIA also reads a footnote in the document as declining to say whether some personalized pricing might be unfair even when fully disclosed, which in their words means "there is no safe harbor." That's their characterization of the footnote, not ours.

EIA's open questions are the ones worth sitting with:

• "Are discounts, coupons, and promotions 'personalized prices'?" — as they put it, "Decades of couponing suggest consumers expect offers to vary from person to person — which should defeat the 'reasonable expectation of uniform pricing' that triggers the entire framework."
• "Where does segmentation end and personalization begin?" — "Is a discount offered to a cohort (new subscribers, lapsed customers, cart abandoners) 'personalized'?"

This isn't a fringe reading. A client alert from Crowell & Moring on August 21 notes the FTC's own definition explicitly names "individualized prices, discounts, coupons or other incentives (e.g., loyalty programs)" as potentially in scope. Discounts are not obviously exempt from the conversation.

Not everyone thinks disclosure is the right remedy in the first place. One of the top comments on the r/technology thread about the proposal argued: "My issue with this is disclosure isn't enough. When you combine businesses without meaningful competition and this price model, the public gets fleeced. Only now, you're being told of being fleeced, and still no protection or consequence."

Where Negotiated Pricing Actually Sits

Here's the honest structural comparison, because "our product is fine, don't worry" isn't an argument.

The behavior the FTC describes has a specific shape: a business uses personal data — browsing history, disposable income estimates, location, device signals — to infer what one individual will pay, then silently shows that person a different number than the listed price everyone else sees. The shopper never sees the personalization happen and never chose to trigger it.

A negotiation flow inverts every part of that:

• Everyone sees the same listed price. The product page price is identical for every visitor. Nothing is computed about anybody.
• The shopper initiates. They click "Make an Offer" and type a number they chose. No personal data goes into producing it.
• The rules aren't personal. Lury's engine is three plain rules against a floor price you set — accept at or above the floor, one single counter at exactly the floor if the offer is within 70%, decline below that. Same logic for every shopper, no AI, no profile. We broke it down in how Lury decides.
• The shopper knows it's theirs alone. An accepted offer produces a single-use code tied to one variant, usage limit 1, expiring in 24 hours. The one-person-only nature is the product.

The "reasonable expectation of uniform pricing" the whole framework hangs on doesn't really get engaged here, because nobody is shown a non-listed price without asking for one. The shopper is the party requesting a different number, deliberately and in the open.

The Part We Should Be Honest About

Our own back catalogue contains a tactic that sits much closer to the line. In lead capture beyond the newsletter, we recommended building a "price-sensitive segment" from declined-offer data and emailing those shoppers later with a discount timed to the price they'd offered. We also lean on declined-offer capture in turning "no" into a lead.

That follow-up email is a discount aimed at a specific person, priced off personal data about them, delivered outside the transparent in-the-moment negotiation. It's precisely EIA's open question about where cohort segmentation ends and personalization begins.

Two things probably make it lower-risk than the FTC's core targets: it's the shopper's own first-party data from a direct interaction with your store, not third-party inferred signals about their income or their behavior at other retailers; and nothing about the discount depth is concealed — the price in the email is the price. But "probably lower-risk" is not "settled," and we'd rather say that than pretend otherwise.

The one thing we'd now call a real mistake: framing that email as a generic "loyalty reward" or "welcome back" discount when it's actually priced off that shopper's specific declined offer. That's the mischaracterized-discount scenario the statement calls out by name.

Practical Steps for Merchants

Two different situations, two different levels of care.

For the core negotiation flow

1. Keep the listed price genuinely uniform. Don't layer geo-based or device-based price variation underneath a negotiation widget. The moment the starting price differs by visitor, the clean argument disappears.
2. Keep the rules impersonal and write them down. Floor price, counter threshold, decline threshold — the same numbers for everyone, documented somewhere you could point to if asked.
3. Make the terms visible at the moment of the offer. Single-use, one variant, 24-hour expiry. Shoppers should understand they're getting a personal price because they asked for one.
4. Don't feed shopper data into the pricing logic. If you ever find yourself wanting to counter differently based on who someone appears to be, that's the point where you've moved into the territory the FTC is describing.

For remarketing off declined-offer data

1. Say why they're getting the offer. "You offered $55 for this last month — it's $56 today" is more honest, and usually converts better, than an unexplained code.
2. Don't dress it up as something it isn't. No "loyalty discount" or "specially selected" labelling on a price derived from that person's own offer history.
3. Stick to first-party data. Their offer, on your store. Don't blend in purchased third-party signals about income or cross-retailer behavior — that combination is the fact pattern the statement describes most directly.
4. Check your privacy policy actually covers it. If you're collecting offer data at submission, including on declined offers, your policy should say what you collect and how you use it.
5. Keep an eye on the docket. Comments close September 25, 2026, and the final statement may look different from the draft.

The Bottom Line

The FTC isn't banning personalized pricing — it can't. It's saying that if a price varies by person in a context where shoppers expect uniformity, you have to tell them it's personalized, why, and what data drove it. A negotiation the shopper starts, on a price everyone else sees too, resulting in a code that's obviously theirs alone, is close to the opposite of the thing being described. The follow-up email you send three weeks later deserves more thought.

Again: not legal advice, and the comment period is still open. If your pricing strategy involves anything more sophisticated than "everyone sees the same number," it's worth a conversation with counsel who's read the actual statement.

If you'd rather offer flexible pricing the transparent way — shopper-initiated, same listed price for everyone, single-use codes with terms shown up front — install Lury on your Shopify store. There's a 14-day free trial, and the negotiation rules are yours to set.