On August 19, 2026, the Federal Trade Commission announced it is seeking public comment on a draft enforcement policy statement targeting "personalized pricing," the practice of using a shopper's personal data to set a price based on what the retailer thinks that individual is willing to pay. The Commission voted 2-0 to publish the draft in the Federal Register, and the public will have 30 days from publication to submit comments.

For small-business owners who sell online, quote services, or use dynamic pricing tools, the draft signals how the FTC intends to police price personalization under existing law. It is not a new rule and it does not ban the practice outright. It is a warning about how the agency reads Section 5 of the FTC Act when a merchant quietly uses customer data to change what a customer pays.

What the FTC actually said

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." In the announcement, FTC Chairman Andrew Ferguson framed the concern this way: "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."

Two points from the draft statement matter most for merchants:

• While the FTC does not claim authority to ban personalized pricing in all cases, the agency notes that failing to disclose the use of personal data to set a price can violate the FTC Act.
• Representing or implying that a price is static when it in fact varies by individual could be a deceptive practice. The draft flags that informed consumers might respond by using a VPN, a private browsing session, or by shopping elsewhere.

The draft also notes that the undisclosed collection or use of personal data for the purpose of personalized pricing "could violate the FTC Act, which prohibits unfair or deceptive practices in the marketplace." Section 5 of the FTC Act is the same authority the Commission uses against hidden fees, deceptive subscription cancellation, and misleading advertising claims.

What is (and isn't) personalized pricing

Not every price change is "personalized" in the FTC's sense. The draft draws a line between prices that change based on market conditions and prices that change based on who is looking at the screen.

Examples the draft would likely treat as ordinary market pricing:

• Surge pricing that applies to every user at a given moment based on demand.
• Regional pricing tied to shipping cost or local tax.
• Time-of-day pricing that applies uniformly to all shoppers.
• Published volume discounts, coupon codes, or loyalty tiers with disclosed terms.

Examples closer to the concern:

• Showing a higher price to a returning visitor because past behavior suggests low price sensitivity.
• Raising a checkout price based on device type, ZIP code inference, or an ad-tech profile.
• Quoting a service estimate based on a scraped income proxy or credit signal without saying so.
• Offering personalized discounts that are described as "promotions" but are actually calibrated to a predicted willingness-to-pay score.

The dividing line the FTC is drawing is disclosure. A merchant that uses personal data to set an individual price and does not clearly say so is the merchant most exposed under this draft.

Why this matters for small businesses

Most small businesses do not build willingness-to-pay models in-house. The exposure comes from the tools they buy. E-commerce platforms, booking systems, CRM add-ons, and AI pricing plugins increasingly market "dynamic" or "smart" pricing features that adjust quotes per visitor. If that adjustment relies on personal data and the storefront still shows a "list price," the small business is the one taking the customer's money, not just the software vendor.

Three practical implications:

1. Check what your storefront actually does. If you use a Shopify app, a WooCommerce plugin, a booking tool, or a quoting tool that offers "personalized pricing," "AI pricing," "price optimization by segment," or "willingness-to-pay modeling," find out what data it uses and what the customer sees. If two customers on identical products see different prices for reasons unrelated to a public promotion, that is the practice the FTC is describing.

2. Disclosure is the cheapest fix. The draft policy is not a ban. It targets the gap between what the shopper thinks is happening and what is actually happening. The mechanism the FTC identifies is a clear, plain-language disclosure placed where the customer sees the price rather than buried in a privacy policy.

3. Contracts with vendors matter. If a pricing vendor's terms leave you responsible for consumer-facing disclosures, you are the party at risk. Ask vendors in writing what personal data feeds the price, whether the price varies per user, and what disclosure language they recommend.

A short self-check

For a practical read on where your business stands, review the checklist below. This is informational only and is not legal advice; consult a qualified attorney about your specific practices.

PERSONALIZED PRICING SELF-CHECK

1. Inventory the tools that touch price
   - Storefront platform (Shopify, WooCommerce, BigCommerce, custom)
   - Any "AI pricing," "dynamic pricing," or "price optimization" apps
   - Booking / quoting software
   - CRM or marketing tools that trigger discount codes per user

2. For each tool, answer:
   - Does the price a customer sees depend on WHO the customer is?
   - What personal data feeds that decision? (email, IP, device,
     purchase history, third-party ad-tech profile, ZIP)
   - Is the same product ever offered at two prices at the same
     moment to two different logged-in users?

3. Review your customer-facing pages:
   - Does the product page or checkout say or imply the price is
     the same for everyone?
   - Where, if anywhere, do you disclose that prices may vary by
     individual customer data?
   - Is that disclosure visible at the price, or only in a footer
     privacy policy?

4. Document your answer to: "If a customer asked me today why they
   saw a different price than their neighbor, what would I say?"

5. Decide:
   - Turn the feature off
   - Keep it and add clear disclosure at the price
   - Restrict it to disclosed, opt-in loyalty or promo mechanics

Paste this checklist into an LLM such as ChatGPT or Claude and ask it to turn it into a working file you can share with your team. Example prompt: "Turn this personalized pricing self-check into a fillable Google Sheet with one row per tool, columns for the questions in step 2, and a status column with a dropdown for Turn Off / Add Disclosure / Compliant. Return it as a Google Sheets template I can copy."

The timeline and how to comment

The FTC's action is procedural at this stage. It is a draft policy statement, not a final rule, and the Commission is asking for public input before finalizing it.

Small-business owners, trade associations, and vendors can submit comments electronically through the Federal Register notice once it posts. If your business or your customers would be affected, for example if you sell software that adjusts prices or you run an e-commerce store that uses one, a comment on the record is the moment to say so. The FTC uses public comments to shape the final statement's scope and enforcement priorities.

What the FTC did not say

Reading the announcement carefully matters, because a lot of coverage will fill in gaps the agency deliberately left open.

The FTC did not:

• Ban personalized pricing.
• Set a dollar threshold, a business-size carve-out, or an industry exemption.
• Announce enforcement actions against specific companies alongside the draft.
• Say that any price variation based on customer characteristics is illegal.
• Address state consumer-protection laws, which may be stricter and which apply regardless of what the FTC finalizes.

The agency's position, as stated, is narrower: undisclosed use of personal data to set a per-individual price can be deceptive or unfair under Section 5, and businesses that do it without telling customers should expect scrutiny.

How Novo customers should think about it

Novo is a fintech offering small-business banking solutions, not a legal advisor, and nothing here is legal advice. But there are two things worth flagging for the accountants, consultants, agencies, contractors, and online sellers who use Novo.

First, if you are a service business that quotes clients individually, such as a bookkeeper, a lawyer, a contractor, or a designer, this draft is not aimed at you. Custom quotes negotiated with a client are not the "hidden per-user price on a listed product" the FTC is describing. Ordinary bidding, custom scopes of work, and negotiated retainers are not personalized pricing in this sense.

Second, if you sell products online or run a booking-based business, this is worth an hour of your time. Look at the pricing apps in your Shopify store. Ask the vendor a plain question in writing: does the price shown to a customer depend on that customer's personal data, and if so, what disclosure do you recommend I show. Keep the answer on file.

Bottom line

The FTC has not changed the law. It has told merchants how it plans to read the law it already enforces when a business uses personal data to charge different customers different prices for the same product without telling them. For small-business owners, the practical response is to know what your pricing tools do, decide whether the practice fits your business, and, if you keep it, disclose it clearly at the price the customer sees.

The primary source for this article is the FTC's August 19, 2026 press release and the linked proposed enforcement policy statement. For questions about how any specific pricing practice applies to your business, consult a qualified attorney.

Disclosures

Novo Platform Inc. ("Novo") is a fintech, not a bank. Banking services provided by Middlesex Federal Savings, F.A., Member FDIC. Eligibility subject to final Novo determination.

Novo Platform Inc. ("Novo") strives to provide accurate information but cannot guarantee that this content is correct, complete, or up-to-date. This page is for informational purposes only and is not financial or legal advice nor an endorsement of any third-party products or services. All products and services are presented without warranty. Novo Platform Inc. does not provide any financial or legal advice, and you should consult your own financial, legal, or tax advisors.