Some Mexican restaurants offer “Taco Tuesday” specials in order to encourage people to eat out on what is usually one of the slowest days for restaurants. These restaurants do not have “Fajita Fridays” because they do not need to offer incentives for people to eat out on Friday. Restaurants and other business determine when to offer discounts and other incentives to attract customers by studying their customers' patterns of behavior.
Modern technology, particularly artificial intelligence (AI), has made it possible for companies to study the buying patterns of individual consumers. Not surprisingly, this practice has been labeled “surveillance pricing” and has garnered opposition from progressives who think that any innovative business practice is a scheme to enable greedy businesses to gain more wealth at the consumer’s expense. The most recent controversy over the use of AI for surveillance pricing (a less inflammatory name for this is “personalized” pricing) occurred in July when Delta Airlines revealed that they use AI to assist in setting prices for approximately 3% of fares. By the end of this year, Delta hopes AI will set as much as 20% of their fares.
U.S. Senators Mark Warner (D-VA), Ruben Gallego (AZ), and Richard Blumenthal (D-CT) wrote a joint letter to Delta inquiring whether it was using AI to gather passengers' personal data to find the individual customer's “pain point.” Pain point refers to the maximum price a consumer is wiling to pay. The letter assumes that consumers have no alternative but to accept whatever price Delta offers. However, consumers can reject that price and force Delta to offer a lower price, by going to another airline or buying from a website offering low prices like Priceline.
As personalized pricing evolves it could lead to a revival of the great tradition of haggling. According to a study by the Federal Trade Commission, companies can use data gained from online purchases, email sign ups, purchase histories, and even locations to find the customer's “pain point.” This allows the business to maximize profits by charging each consumer the highest price the consumer is willing to pay. But consumers have the ability to reject the offered price. Another problem is that this “pain point” calculation is based on past data that may no longer reflect the consumer's current situation. For example, someone may have paid higher than average airfares in the past because they had to fly across the country to deal with a family emergency. This does not mean they are willing or able to pay an above average fare for their vacation flight.
The best example of personalized pricing is ride sharing companies like Uber and Lyft. These companies adjust their prices based on the time of day (expect to pay more for a ride during rush hour or on a weekend evening than at other times), the number of available drivers, and the length of the trip. Some have accused ride-sharing apps of charging more to customers they determine have a low cell-phone battery. Uber denies this practice but does admit that their data shows that passengers whose phone batteries are low are more willing to pay more than other customers.
It makes sense that someone with a low phone battery would be more in need of a quick pickup—and thus willing to pay more—than someone with a charged battery. The higher price encourages drivers to make that ride a priority, thus benefiting the passenger, the ride sharing company, and the drivers. This is how a market is supposed to work.
The FTC study was done under the reign of litigation- and regulation-happy Chair Lina Khan. The agency has not done anything regarding personalized pricing since Andrew Ferguson, President Trump’s pick to head the FTC, became Chair in January. Democrat Representatives Greg Casar (TX) and Rashida Talib (MI) have introduced the . This legislation bans setting prices or wages based on surveillance data defined as “personal information, genetic information, behavior, or biometrics.” The bill is unlikely to be voted on in the Republican Congress. However, it could be considered if the Democrats regain control of the House in 2026.
Several state legislatures have introduced legislation to ban surveillance pricing. New York has passed legislation forbidding landlords from using “algorithms” to set rents. Surveillance or personalized pricing can benefit consumers by enabling businesses to offer their goods and services at a price the consumers' data suggests they are willing and able to pay. Consumers always have the option of saying no or asking for a lower price. This is how markets are supposed to work. The real danger to our liberty is not the surveillance done by businesses—but the surveillance done by government.
