Gasoline and other retailers are using artificial-intelligence software to set optimal prices, testing textbook theories of competition; antitrust officials worry such systems raise prices for consumers
“This is not a matter of stealing more money from your customer. It’s about making margin on people who don’t care, and giving away margin to people who do care…”
ROTTERDAM, the Netherlands—One recent afternoon at a Shell-branded station on the outskirts of this Dutch city, the price of a gallon of unleaded gas started ticking higher, rising more than 3½ cents by closing time. A little later, a competing station 3 miles down the road raised its price about the same amount.
The two stations are among thousands of companies that use artificial-intelligence software to set prices. In doing so, they are testing a fundamental precept of the market economy.
In economics textbooks, open competition between companies selling a similar product, like gasoline, tends to push prices lower. These kinds of algorithms determine the optimal price sometimes dozens of times a day. As they get better at predicting what competitors are charging and what consumers are willing to pay, there are signs they sometimes end up boosting prices together.
Advances in A.I. are allowing retail and wholesale firms to move beyond “dynamic pricing” software, which has for years helped set prices for fast-moving goods, like airline tickets or flat-screen televisions. Older pricing software often used simple rules, such as always keeping prices lower than a competitor.
On the Same Track
Two competing gas stations in the Rotterdam area both using a2i Systems pricing software roughly mirrored each other’s price moves during a selected week.
These new systems crunch mountains of historical and real-time data to predict how customers and competitors will react to any price change under different scenarios, giving them an almost superhuman insight into market dynamics. Programmed to meet a certain goal—such as boosting sales—the algorithms constantly update tactics after learning from experience.
Ulrik Blichfeldt, chief executive of Denmark-based a2i Systems A/S, whose technology powers the Rotterdam gas stations, said his software is focused primarily on modeling consumer behavior and leads to benefits for consumers as well as gas stations. The software learns when raising prices drives away customers and when it doesn’t, leading to lower prices at times when price-sensitive customers are likely to drive by, he said.
“This is not a matter of stealing more money from your customer. It’s about making margin on people who don’t care, and giving away margin to people who do care,” he said.
Driving the popularity of A.I. pricing is the pain rippling through most retail industries, long a low-margin business that’s now suffering from increased competition from online competitors.
“The problem we’re solving is that retailers are going through a bloodbath,” said Guru Hariharan, chief executive of Mountain View, Calif.-based Boomerang Commerce Inc., whose A.I.-enabled software is used by StaplesInc. and other companies. Staples uses A.I.-enabled software to change prices on 30,000 products a day on its website. PHOTO: RICHARD B. LEVINE/ZUMA PRESS
The rise of A.I. pricing poses a challenge to antitrust law. Authorities in the EU and U.S. haven’t opened probes or accused retailers of impropriety for using A.I. to set prices. Antitrust experts say it could be difficult to prove illegal intent as is often required in collusion cases; so far, algorithmic-pricing prosecutions have involved allegations of humans explicitly designing machines to manipulate markets.
Officials say they are looking at whether they need new rules. The Organization for Economic Cooperation and Development said it plans to discuss in June at a round table how such software could make collusion easier “without any formal agreement or human interaction.”
“If professional poker players are having difficulty playing against an algorithm, imagine the difficulty a consumer might have,” said Maurice Stucke, a former antitrust attorney for the U.S. Justice Department and now a law professor at the University of Tennessee, who has written about the competition issues posed by A.I. “In all likelihood, consumers are going to end up paying a higher price.”
In one example of what can happen when prices are widely known, Germany required all gas stations to provide live fuel prices that it shared with consumer price-comparison apps. The effort appears to have boosted prices between 1.2 to 3.3 euro cents per liter, or about 5 to 13 U.S. cents per gallon, according to a discussion paper published in 2016 by the Düsseldorf Institute for Competition Economics.
Makers and users of A.I. pricing said humans remain in control and that retailers’ strategic goals vary widely, which should promote competition and lower prices.
Sectors with fast-moving goods, frequent price changes and thin margins—such as the grocery, electronics and gasoline markets—have been the quickest to adopt the latest algorithmic pricing, because they are the most keen for extra pennies of margin, analysts and executives say.
