When the Price Tag No Longer Means One Price
For most purchases, consumers expect a simple rule. The price on the tag is the price everyone pays.
There have always been exceptions. Airline tickets, hotel rooms, and concert seats often fluctuate depending on demand. A passenger booking a flight months in advance may pay far less than someone reserving a seat the day before departure.
Those situations follow a familiar economic logic. Supply and demand determine price.
A new pricing model is now emerging across the digital economy. Instead of adjusting prices only for market demand, companies are increasingly using data and algorithms to adjust prices for individual customers.
The Rise of Personalized Pricing
Advances in data analytics allow companies to track detailed information about consumers, including location, purchase history, and spending patterns.
Businesses can feed that information into algorithmic systems that adjust pricing in real time.
A retailer might charge slightly more to customers ordering from affluent neighborhoods. A delivery platform might increase service fees for users with premium credit cards. These differences are often small enough that customers may never notice.
The concept has been described by critics as “surveillance pricing.”
A Simple Experiment With Fast Food
To see how variable pricing might appear in everyday transactions, a group of journalists conducted a small experiment using a food delivery platform.
Six colleagues placed the same order at the same time from the same location in Manhattan. Each person ordered a Big Mac meal with fries and a drink from the same McDonald’s restaurant.
The expectation was simple. Everyone should pay the same price.
That did not happen.
When the receipts arrived, the total bills differed slightly. The differences were small, around 15 to 20 cents, but they were consistent.
Where the Price Differences Appeared
The base price of the Big Mac meals remained identical across all orders.
The difference appeared in the service fee charged by the delivery platform.
Some users paid $3.25, while others paid $3.45, even though two of the orders were delivered by the same driver.
There was no clear pattern explaining who paid more.
Age, income level, and gender did not appear to correlate with the price differences.
Companies Often Provide Limited Explanations
When asked about the differences, the delivery platform said that fees can vary but are not based on personal characteristics.
However, the company’s app also includes a disclosure for New York users stating that pricing may be determined by algorithms using personalized data.
The disclosure exists because of a New York law requiring companies to inform consumers when algorithmic pricing is used.
The company said the warning reflects legal compliance rather than a specific pricing practice.
Lack of Transparency Around Algorithmic Pricing
Experts say it is difficult to determine how widespread personalized pricing has become because companies rarely disclose how their algorithms operate.
Oren Bar-Gill, a professor of law and economics at New York University, says many businesses are investing heavily in consumer data.
Retailers collect detailed information about user behavior because that data can help them optimize pricing strategies.
“Retailers are paying a lot of money to obtain personalized consumer information,” Bar-Gill says. “They are doing it for a reason.”
Research Into Algorithmic Pricing
A 2025 report from the Federal Trade Commission attempted to map the technology ecosystem behind algorithmic pricing.
The research suggested that companies across multiple industries are experimenting with pricing systems that adjust automatically based on consumer behavior and data signals.
Even when the price differences are small, they can add up significantly when applied across millions of transactions.
Why E-Commerce Makes It Easier
Personalized pricing would be difficult to implement in traditional retail stores.
When customers stand in line at a physical checkout counter, everyone can see the price printed on the product or displayed on a shelf.
Online shopping creates a completely different environment.
Digital platforms can modify prices invisibly, adjusting fees during checkout or embedding them in service charges that appear only in the final steps of an order.
Consumers often do not notice the difference unless they directly compare receipts.
Small Fees, Large Impact
In the McDonald’s experiment, the price differences were tiny. A few extra cents would not discourage anyone from ordering lunch.
However, those small adjustments become significant at scale.
A difference of 20 cents per order, multiplied across millions of transactions, can generate substantial additional revenue for digital platforms.
A Pricing System Few People Understand
Despite growing concerns about algorithmic pricing, the public still knows relatively little about how it works.
Companies rarely explain the details of their pricing algorithms, and regulators are only beginning to examine the practice.
For consumers, the biggest challenge may simply be visibility.
Prices may already be changing from one user to another.
The difference is that many customers may never realize it.
Source: BI
