Dynamic pricing changes in response to market conditions such as demand, inventory, timing, or competitor prices. Personalized pricing uses personal data to estimate what an individual consumer may be willing to pay, then tailors that person’s price or offer. Since both can make prices differ between shoppers, a price difference alone does not show which method was used. The key question is what caused the price to change.
How the two pricing methods differ
| Question | Dynamic pricing | Personalized pricing |
|---|---|---|
| What drives the price? | Market conditions such as demand, supply, inventory, time, availability, or competitor prices. | Personal data used to infer an individual’s or group’s likely willingness to pay. |
| Would comparable shoppers see the same offer? | Under the EU Commission’s guidance, shoppers viewing the same product at the same time should see the same price when pricing is dynamic but not personalized. | Offers can differ because a seller uses information about a person or group to tailor a price or promotion. |
| Typical example | An event ticket becomes more expensive as seats sell, or a hotel rate changes with availability. | A seller adjusts an offer using a shopper’s browsing or purchase profile. |
The OECD describes online personalized pricing as a form of price discrimination in which consumer data helps a seller estimate willingness to pay. Dynamic pricing instead responds to changing market factors. These approaches are distinct, but a seller could use market conditions and personal data in pricing; seeing a changed price does not reveal which inputs were used. OECD, Protecting Digital Consumers: Delivering Better Policies Through Behavioural Insights; European Union, Your Europe: Unfair pricing.
What can cause prices to vary?
Market conditions: dynamic pricing
Prices for flights, inter-city rail, event tickets, ride services, and hotel rooms may shift as time passes, demand changes, or available capacity becomes scarce. Two people can therefore encounter different prices if they shop at different times, even if neither person’s profile affects the price.
Personal information: personalized pricing
A seller may use information such as browsing or search history, device details, location, demographics, purchase history, or observed shopping behaviour to tailor a price or promotion. In an initial study update in January 2025, FTC staff said documents from pricing intermediaries indicated that data such as location, demographics, browsing patterns, shopping history, mouse movements, and items left in an online cart could be used to tailor prices. The FTC described its examples as hypothetical and said its study was ongoing; they do not establish that a named retailer charged a particular customer a particular price. FTC, January 2025 initial study update.
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How to investigate a price difference
- Compare like with like. Check the same product or service, seller, location, sales channel, and moment as closely as possible. Taxes, delivery, optional features, inventory, and timing can change the total or the offer.
- Look for what changed. A change that tracks time, demand, inventory, availability, or competitor prices points toward dynamic pricing. A change that tracks someone’s browsing or purchase profile points toward personalization. These clues are not proof by themselves.
- Check the full price and conditions. Compare the total payable amount and any eligibility rules, discount terms, or optional extras—not just a headline price. FTC guidance says businesses may use demand- or inventory-based dynamic pricing if the pricing information is not misleading; discounts unavailable to everyone should not obscure the price offered to everyone. FTC, The Rule on Unfair or Deceptive Fees: Frequently Asked Questions.
- Treat a mismatch as a reason to investigate, not a verdict. Location, sales channel, timing, and other differences can confound comparisons. Different prices at the same time do not, on their own, establish that personal data caused the difference.
What the evidence can—and cannot—show
Personalized pricing can benefit one shopper with a lower tailored offer and disadvantage another with a higher one. Its effects depend on market conditions and the seller’s motives; consumers may also find it difficult to detect personalization or know whether their price is higher or lower than the one they otherwise would have received.
The prevalence evidence needs careful dating. An OECD chapter reported few irrefutable examples of online personalized pricing and no evidence at that time that it was widespread, while noting that detection is difficult. That is a historical finding, not a current estimate for 2026. The FTC’s January 2025 update described intermediary capabilities and hypothetical examples, not a representative measure of how often consumers receive personalized prices. Neither source establishes a reliable current prevalence percentage.
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What disclosure rules say in the EU and United States
European Union
The EU’s Your Europe consumer guidance says traders must inform consumers when a price is personalized through automated decision-making and profiling of specific consumer behaviour. The guidance says personalized pricing is not categorically illegal and describes a transparency entitlement; it was last checked on April 30, 2026. This is EU guidance and should not be assumed to describe the law elsewhere. Your Europe: Unfair pricing.
United States
In August 2026, the FTC sought public comment on a draft enforcement policy statement. The agency defined personalized pricing as using personal data to set prices based on what a company thinks an individual is willing to pay, and said undisclosed use of personal data for that purpose could violate the FTC Act. In September 2026, the FTC extended the comment deadline to September 25, 2026. These releases describe a proposed statement and the agency’s view of existing-law enforcement; they do not establish a categorical federal ban or the proposal’s later disposition. FTC, August 2026 draft policy announcement; FTC, September 2026 comment extension.
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