Surveillance Pricing: When the Price Is a Guess About You

You found the flight, the hotel or the grocery order, and the price looked fair. You clicked “buy” and moved on with your day. But what if the number on your screen wasn’t the price? What if it was a guess about you?

That’s the heart of surveillance pricing: using what a company knows about you, like your location, your device, your browsing and your purchase history, to set a price for you specifically. Not the price for the item. The price for the person. And if you’re a hard-working family that pays the bills, buys what you need and rarely argues at checkout, the system may have already decided you’re someone who will pay a little more.

What Surveillance Pricing Actually Is

When the Federal Trade Commission ordered eight companies to hand over information in July 2024, it described these tools in plain terms: products that use algorithms, artificial intelligence and personal information about consumers, “such as their location, demographics, credit history, and browsing or shopping history,” to categorize people and set a targeted price for a product or service.

That’s different from ordinary dynamic pricing, and the difference matters:

• Dynamic pricing moves the price for everybody based on the market. Rideshare prices jump during a storm. Hotel rates climb on a big game weekend. Everyone looking at the same moment sees roughly the same number.
• Surveillance pricing moves the price for you based on you. Two people looking at the same item, at the same store, at the same moment, can see different numbers because a system has sized each of them up.

One is supply and demand. The other is a profile. And the profile never tells you it exists.

What the Record Shows So Far

I’m not going to hand you rumors. Here’s what has actually been documented.

The federal study. In January 2025, FTC staff released preliminary findings from that study of pricing “middlemen,” the firms retailers hire to tune their prices. Staff reviewed documents from Mastercard, Accenture, PROS, Bloomreach, Revionics and McKinsey & Co. They found that details like a person’s precise location or browsing history can be used to target people with different prices for the same goods and services, and that behaviors as small as mouse movements on a webpage, or the items you leave sitting in an online cart, can be tracked and used to tailor pricing. Staff also noted these intermediaries worked with at least 250 clients, from grocery stores to apparel retailers. One example from the FTC: a shopper profiled as a new parent may be intentionally shown higher-priced baby thermometers on the first page of search results.

The older receipts. This isn’t brand new. In 2012, the Wall Street Journal found the Staples website showing different prices for the same stapler depending on the shopper’s estimated location, often with lower prices when a rival store was nearby. That same year, the Journal reported that Orbitz had begun showing Mac users different, sometimes costlier, hotel options than PC users, after finding Mac users tended to spend more per night. Orbitz said it wasn’t charging different people different prices for the same room. But notice what the system learned: your device says something about your wallet.

The grocery cart test. In December 2025, Consumer Reports and the Groundwork Collaborative published an investigation in which 437 volunteers shopped Instacart at the same stores at the same time. They found prices for the same items varying by as much as 23%. In one Seattle test, the same basket from the same store cost some shoppers $114.34 and others $123.93. Instacart said those were randomized pricing tests, not based on personal data or demographics, and it ended the program that same month. Whatever the input, the lesson is the same: the price on your screen may not be the price your neighbor sees.

The regulators. Across two different FTC leaderships, the agency has now flagged this practice. In August 2026, the Commission voted to propose an enforcement policy statement warning that using personal data to set individualized prices without adequate disclosure may be an unfair or deceptive practice under federal law, and it asked the public for comment. That statement is still a proposal, not a final rule.

The states. New York’s Algorithmic Pricing Disclosure Act took effect November 10, 2025. It requires businesses that set prices with an algorithm using a consumer’s personal data to display a notice near the price: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” A federal court rejected a retail trade group’s challenge to it in October 2025. In 2026, three states went further and restricted the practice itself. Maryland’s law, signed in April, limits large grocery stores and delivery services from using personal data to set grocery prices for specific shoppers, starting October 1, 2026. Connecticut enacted a broader restriction in June that takes effect July 1, 2027. New Jersey’s Fair Price Protection Act, signed in July, targets grocery pricing, with most provisions taking effect in August 2027. Each law has exceptions, loyalty programs and discounts among them, so check your own state’s rules before assuming you’re covered.

Why Surveillance Pricing Is Slave Arithmetic in a New Suit

At Be Free University we talk about Slave Arithmetic: the math where housing, transportation, taxes, debt and insurance add up to 100% of your income before you’ve bought a single bag of groceries. It’s a system where your money is spoken for before it ever reaches your hand.

Surveillance pricing is that same math with a new tool. In the old model, the price was set by what the thing cost plus a margin. In this model, the price can be set by what a system predicts you’ll tolerate. The FTC’s own proposed statement describes personalized pricing as setting prices based on a consumer’s estimated willingness to pay or likelihood of comparison shopping.

Read that twice. Likelihood of comparison shopping. The shopper who’s too busy to compare, too tired to check, too loyal to leave, is the shopper the math is built around. That’s a lot of good, hard-working people. You’re not careless. You’re busy. And busy has a price tag.

This is why I keep saying you’re not bad with money. The system was never designed for you to keep it. They taught us Slave Arithmetic. We teach Owner’s Math.

Worked Numbers: What a Quiet Markup Costs You

These numbers are illustrative, not a measurement of any company or household. Picture a couple earning $110,000 a year. Between groceries, household goods, travel and everyday online orders, they spend about $1,200 a month through apps and websites that could personalize prices.

• If a personalized markup averaged just 4%: $1,200 × 4% = $48 a month.
• $48 × 12 months = $576 a year.
• $576 × 10 years = $5,760, and that’s before you count what that money could have earned working for you.

Now look at the real grocery test above. The gap between $114.34 and $123.93 is $9.59. If a family paid that kind of difference on one weekly grocery order: $9.59 × 52 weeks = $498.68 a year. Nobody would notice $9.59. Everybody would notice $500.

That’s how this works. It’s not one big theft. It’s a hundred small markups you never agreed to, collected quietly because the system bet you wouldn’t check.

The Owner’s Math Response

This is a Release Your Flow issue, the cash flow pillar of the F.R.E.E.D.O.M. Framework. Releasing your flow means you decide where your money goes before the system decides for you. And the most powerful position in any negotiation, including the silent one happening on your screen, belongs to the person who can walk away.

Think about who this pricing favors. It favors urgency. It favors convenience. It favors the shopper who has to buy right now. Owners build margin into their lives so they’re rarely in a hurry. When you have a cushion, a plan and a list, you get to wait for the better price, check another store or skip the purchase entirely. If you haven’t mapped your monthly spending, start with where your money really goes every month. You can’t defend a flow you can’t see.

“The wise store up choice food and olive oil, but fools gulp theirs down.” (Proverbs 21:20, NIV)

Storing up isn’t just saving. It’s refusing to be rushed.

Your Next Move: Defenses Against Surveillance Pricing

No single trick beats every pricing system, and I won’t pretend one does. Some companies may not personalize at all, and others use signals you can’t easily hide. But these habits are reasonable, free and put friction back on your side:

1. Compare before you commit. For bigger purchases like flights, hotels, electronics and appliances, check the price logged in and logged out, in a private browsing window and on a second device. If the numbers differ, you’ve learned something. If they don’t, you’ve lost two minutes.
2. Clear cookies and limit tracking. Clear your browser cookies periodically and review the privacy settings in the browsers and shopping apps you use most. It won’t erase what a company already knows about your account, but it shrinks the trail you leave for everyone else.
3. Turn off location access for shopping apps. On your phone, set shopping and delivery apps to use location only while the app is open, or not at all when you don’t need delivery. Precise location was among the data types the FTC flagged.
4. Track prices and keep your receipts. Use a price-tracking tool or simply screenshot prices before you buy. Save receipts and order confirmations. Some retailers offer price adjustments within a window, and a record helps you ask for one. If you live in New York, watch for the required algorithmic pricing notice near the price.
5. Build the margin to walk away. The FTC listed credit history among the data these tools can use, and urgency is what personalized pricing feeds on. A real emergency fund and a plan for your cash flow mean you’re rarely forced to buy today at whatever price the screen decides. That’s the defense no algorithm can override.

If you want the bigger picture of how fixed costs squeeze your month, read the 100 percent trap, then come back and run these five steps.

From Profiled to Prepared

The system is getting smarter about you. That’s the reality. But it only wins when you stay predictable, rushed and unaware. The moment you start comparing, pausing and planning, you stop being the customer the algorithm was betting on and start being the owner who sets the terms.

You don’t have to fear the machine. You just have to stop being in a hurry. Build the margin, guard your data, and let every dollar you keep go to work for your family instead of someone else’s model.

— George M. Howard Jr., “Financial Moses”
Founder, Be Free University