The Washington Post is setting prices 'based on personal data.' What is dynamic pricing, and how are they deciding how much to charge you?

The single line, first highlighted in a Washingtonian investigation, has pulled back the curtain on a pricing strategy that many consumers don’t realize is already shaping what they pay for groceries to airline tickets (1).

From surge pricing to “surveillance pricing”

Dynamic pricing isn’t new.

Airlines have long adjusted ticket prices based on demand. Ride-hailing apps also increase fares during busy periods. Meanwhile, hotels charge more during peak travel seasons.

Traditional dynamic pricing responds to market factors like time, inventory and demand.

Thanks to the advancements in AI, it’s possible for companies to set prices based on your online behavior. Regulators increasingly refer to this as “surveillance pricing.”

According to a January 2025 Federal Trade Commission (FTC) study , companies are already using personal data — including browsing history, location and even mouse movements — to tailor prices to individual consumers (2). In some cases, two people may see different prices for the same product, depending on who they are and how they behave online.

“Retailers frequently use people’s personal information to set targeted, tailored prices,” FTC Chair Lina Khan said in the report.

What data are companies using?

The Washington Post has not publicly detailed its pricing algorithm. However, Luca Cian, a University of Virginia business professor, told The Washingtonian that such systems typically rely on a mix of demographic signals, behavioural data, and inferred income (1).

These factors can include:

• Device type: Using an iPhone may signal a higher income than using an Android device
• Location data: IP addresses can be cross-referenced with housing values through Zillow to estimate wealth
• Reading behaviour: Frequent users are charged more because they appear to value the service more
• Subscription history: Whether you renew, cancel or engage inconsistently.

In other words, the algorithm is estimating how much you personally are willing to pay.

The Post’s disclosure stands out because most companies don’t explicitly tell customers about dynamic pricing, but the practice is widespread.

Amazon changes prices several times per day based on market demand (3). Delta Air Lines has said it aims to have 20% of domestic fares set using AI-driven systems. Instacart previously tested pricing models that led some customers to pay more than others for identical grocery items (4,5).

The FTC’s findings suggest these differences aren’t random. Companies can track customer behaviour, such as what you leave in your cart, how long your cursor hovers over a product, or whether you’ve searched for similar items elsewhere (2).

Can you avoid it?

In theory, yes — but it’s difficult.

The Washingtonian reports that most consumers willingly hand over large amounts of data when they accept the user agreement. Avoiding personalized pricing would require limiting that data trail (1).

Some tactics may help include:

• Using a VPN to mask your location
• Browsing in private or incognito mode
• Switching devices or avoiding logged-in sessions

Modern pricing systems rely on a wide web of signals, and avoiding them entirely can be inconvenient or impractical.

As Cian told Washingtonian, achieving meaningful privacy would require “a lot of effort” — something very few consumers are likely to do (1).

What regulators are doing next

Governments are starting to respond, though regulation remains fragmented.