When the algorithm sees your wallet, prices may be higher. Dynamic pricing can cause a wave of outrage

Ashley Davis05/01/2026

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In recent years, customers have become accustomed to prices rising, but they are not used to the feeling that they are growing unevenly and for no clear reason. This is where dynamic pricing comes in – price changes driven by algorithms – and its more controversial variant, personalized pricing (sometimes called surveillance pricing), where signals about you and your habits influence how much you pay.

The US Federal Trade Commission (FTC) explicitly examines this market and indicates that companies can use a wide range of consumer data to set individualized prices.

In December 2025, Instacart announced the end of pricing tests powered by AI tools after criticism and pressure from regulators. Investigations by consumer organizations have shown that some people saw prices up to 23%. higher for the same products at the same time and store, and the FTC became interested in the case.

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Regardless of whether the company calls it testing, optimization or limited promotions, the effect in the eyes of customers is the same: the feeling that the rules of the game are hidden.

Why is this so emotional? Because price is not only a number for people, but also a message about honesty. When the algorithm changes the amount in the background and the customer does not understand the logic, the worst interpretation is triggered. Specifically: “I pay more because they recognized me.” Several years ago, the OECD described the risks of personalized prices in the digital economy, pointing out, among others, to information asymmetry, potentially unfair practices and the growing importance of consumer protection.

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This is unfair treatment of customers

European research on online segmentation pointed out that personalization can use, among others: browsing data and lead to more expensive results or offers for users considered more affluent.

In 2026, scale will be at stake. Strategic advisors and industry forecasters agree on one thing. AI is becoming more and more common is designed to drive near real-time trading decisions, including pricing and promotionbecause it is a quick way to improve margins. BCG describes that switching to AI-powered pricing and dynamic pricing models can increase gross profit and at the same time improve the perception of value. But this only works if the company does not destroy trust.

The problem is that The line between wise promotion and price discrimination is invisible to the customer. And when customers feel watched, they become defensive. Experimental research shows that consumers can respond strategically to personalized prices – they try to manipulate signals, limit disclosures, change behavior if they suspect that the system is “reading” their profile.

In practice, this means the growing popularity of VPNs, private mode, blocking trackers and cookies, comparing prices on different devices, and even moving purchases to places where the price appears to be the same. But it's also a spiral. Why? The more companies rely on user data, the more users will do anything not to leave it behind – even at the expense of convenience.

What about regulations?

In Europe there is also a regulatory aspect. The revised EU rules require the seller to inform the consumer if the price offered has been personalized on the basis of automated decision-making.

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This does not solve the entire problem (because the information may be given in small print and too late), but it sets a certain direction. Prices may change, but they cannot be a secret customer selection mechanism.

At the same time, regulators in various countries are stepping up enforcement of transparency in online pricing practices – the British CMA has just launched a broad offensive against misleading pricing practices in e-commerce.

What are the most important threats and recommendations? On the consumer side, it is necessary to assume that the price on the screen is not always an objective priceonly an offer placed in context. Therefore, it is worth developing the habit of checking the price in more than one place and time and treating excessive personalization as a warning signal. If a store requires too many consents, tracks activity outside its website, or changes amounts “weirdly,” privacy costs may be added to the bill.

At the same time, you must remember that VPNs themselves are not a magic cloak of invisibility. Modern device identification techniques can also work beyond an IP address, so the best strategy is to limit tracking more broadly, not with one trick.

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On the corporate side, the recommendation is brutally simple. In the era of algorithms, the winner is not the one who most accurately squeezes the willingness to pay, but the one who does it without losing trust. Dynamic pricing is defensible when customers see the benefit (e.g. off-peak discounts, clear rules, limiting fluctuations, fair justification for price increases), and not when they feel profiled. In addition, there is data hygiene. The more the price depends on behavioral data, the greater the reputational and legal risk – especially if the algorithm indirectly differentiates people by sensitive characteristics or exploits their vulnerabilities.