Surveillance pricing: when the price tag is about you, not the product

You look up a flight in the morning. You come back at lunch to book it, and the fare has crept up. You blame demand. Later a friend pulls up the exact same hotel, at the exact same moment, on their phone — and sees it cheaper than you do. That one's harder to explain away.

It usually isn't a glitch, and it isn't only supply and demand. It's a practice with a plain, unsettling name: surveillance pricing. The shop isn't pricing the product. It's pricing you.

What it actually is

Surveillance pricing is the practice of setting an individual price from the personal data a company has collected about you — your location, your device, your browsing history, your past purchases, sometimes an estimate of your income. The goal, stated bluntly by economists, is to find your "pain point": the highest number you'll accept before you walk away, and then to show you that number.

It's worth separating this from a thing you already know and mostly tolerate. Dynamic pricing — airline fares, hotel rooms, Uber's surge — moves with time, demand, and supply. Everyone standing in the same market at the same moment sees roughly the same shift. Surveillance pricing is different in kind: two people in that same market, at that same moment, see different numbers, because the difference is them.

"We are approaching a world in which each consumer will be charged a personalised price for a personalised product or service." — Oren Bar-Gill, legal scholar and economist, NYU

How the machine reads you

None of this works without data, and the data comes from everywhere at once. Cookies and browser fingerprinting. Mobile apps that quietly read your location and device. Loyalty cards that log every purchase. Your IP address, your browser's language, the exact model of phone in your hand. All of it feeds an algorithm that scores your price sensitivity — how much your behaviour is likely to change when the number goes up.

The unsettling part is how little a signal has to be to count. In its 2024 study of the practice, the US Federal Trade Commission catalogued the kinds of moves retailers watch for, and they read less like accounting and more like someone reading your face:

Newer buyers get flagged as "less savvy" and steered toward worse rates. Loyal customers get excluded from discounts, precisely because the model believes they'll buy anyway. AI didn't invent the idea of charging each person their maximum — it just made it possible to do at the scale of every shopper, every second.

It's already happening

This isn't a forecast. The receipts already exist:

• Target agreed to pay $5 million after its app was found to raise prices based on location — reportedly charging about $100 more for a TV once you were in the parking lot.
• Amazon changes prices more than 2.5 million times a day. Back in 2000 it ran a price test that showed different DVD prices to different shoppers; after the backlash, Bezos apologised and called it a mistake.
• Orbitz steered Mac users toward pricier hotels, on data suggesting Mac owners spend more.
• Staples showed higher prices to shoppers in areas with fewer nearby competitors.
• Delta said in 2025 that AI already sets around 3% of its domestic fares, and it wants that at 20% — prompting three US senators to warn of pricing tuned to each traveller's "pain point."
• Instacart was found running AI price experiments in which shoppers buying the same items from the same store at the same time saw different prices. It said it was ending the tests.

Why it stings more than a sale

Coupons, student discounts, off-season fares — we live with all of it, because it's visible and it points one way: toward a lower price for someone who needs it. Surveillance pricing runs the other way. It's built to find higher prices, it aims them at whoever the model thinks is cornered, and — this is the core of it — you almost never know it happened. There's no label, no way to compare your number against anyone else's.

Now push it one step further, past "annoying" and into "wrong." The same profiling can lean on the traits it absolutely shouldn't. Charge more in a low-income neighbourhood, and price discrimination lands hardest on the people with the least room to absorb it. Learn someone has celiac disease, and a shop could quietly mark up the gluten-free food they can't safely do without. The market for this data has genuinely dark corners — one woman began receiving ads for cremation services after finishing chemotherapy, apparently because a broker had put her on a list of people with a terminal illness. That's the same machinery, pointed at your vulnerabilities on purpose.

Coming to a shelf near you

For now this mostly lives online, because a paper price tag can't change as you approach it. That's changing. Electronic shelf labels — already in Walmart and Whole Foods — can update in real time. Loyalty apps that hand out personalised coupons are the friendly first step: temporarily lower prices in exchange for a permanent stream of your data. The worry experts name is the obvious next one — cameras on the shelf estimating age, gender, and mood, and a price that shifts for whoever's standing there with the store's app open. Retailers have held back so far, mostly for fear of the backlash. "The new normal" is one analyst's phrase for where it drifts if we shrug.

The law is scrambling

Regulation is chasing the technology and falling behind. The picture, roughly:

• United States — no federal law aimed squarely at personalised pricing. The FTC studied it and sounded the alarm under one administration, then largely dropped it under the next. States are filling the gap: dozens of bills across two dozen states in a single year. New York now requires a blunt disclosure when personal data sets a price — "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA." California's attempt to ban the practice outright was mostly struck down after heavy industry lobbying.
• European Union — the GDPR doesn't ban personalised pricing, but its rules on consent, profiling, and automated decisions make companies far more cautious, and dynamic pricing generally has to be disclosed.
• United Kingdom — new competition powers let the regulator fine firms up to 10% of global revenue for unfair or hidden pricing practices.
• Canada — proposed privacy reform points the same way, and Manitoba moved to become the first province to ban the practice.

"It's predatory, it's discriminatory, and it violates a public trust when consumers are already stretched thin and don't deserve to be unwittingly exploited." — Christopher Ward, California Assemblymember

How to be a smaller target

You can't opt out of this on your own, and it would be dishonest to pretend otherwise. But surveillance pricing runs on data, and you can starve it of some. A few things that genuinely help:

• Prefer a browser over an app. Apps hoover up far more about you — location, device details, behaviour — and send it straight home. A browser leaks a fraction of that, and can add tracking and fingerprinting protection on top.
• Block third-party cookies. They exist almost entirely to follow you between sites. Turning them off removes a chunk of the profile.
• Use a VPN. It hides your IP address — one of the most revealing things about you — and stops your internet provider from logging and selling where you go.
• Comparison-shop across devices. Check the same thing on a different device or browser, ideally logged out. A gap between the two is the practice showing itself.

The honest caveat, which the FTC makes too: even these can be defeated. Device fingerprinting identifies you from the unique mix of your hardware and settings, no cookie required. Individual defence buys you privacy at the margins. The thing that actually reins this in is rules — which is exactly why the disclosure laws, and the fights over them, are worth watching.

Why we're writing this down

We build small tools at Sadapanna, and we hold every one of them to a simple rule: keep your data on your device where we can, collect only what a thing genuinely needs, and never sell it. Surveillance pricing is what the opposite rule looks like when it's followed all the way to its end — every signal harvested, every profile monetised, the price itself turned into an instrument for reading how much it can get out of you.

The fix isn't paranoia. It's noticing. A price is supposed to describe a product. When it starts describing you instead — quietly, and without your say — that's worth seeing clearly, and worth saying out loud.