Is algorithmic pricing fair to consumers?

When Oasis released the tickets for their highly anticipated 2024 reunion tour, fans scrambled to be the first to buy tickets before they sold out. But many voiced concerns that prices were shooting up. At the time, customers wondered if the so-called ‘dynamic pricing’ was at play—where an algorithm alters prices in real time depending on market conditions. Yet the UK Competition and Markets Authority (CMA) later found no evidence that Ticketmaster had used an algorithm to adjust prices. Instead, the cheapest tickets sold first, and then the more expensive ones. Algorithmic pricing may not have been used for the Oasis tickets, but it does exist. How are consumers supposed to know when a machine is dictating prices? And if they don’t understand how prices are determined, they may perceive them as unfair.

Companies are increasingly using software to automate the prices their customers see. In a recent paper published in the International Journal of Research in Marketing, Esade’s professor Marco Bertini, along with several fellow researchers, examined what happens when pricing becomes increasingly automated. They define algorithmic pricing as the use of programs to automate the setting of prices. This isn’t merely a technological upgrade; it’s a strategic decision that affects customers, competition, organizational processes, and regulation.

Algorithms can make pricing smarter—but customers may not agree

From the perspective of businesses, the benefits of using a pricing algorithm mean they can process huge quantities of information and adjust prices at lightning speed. An algorithm can assess demand, supply, competitor prices, customer behavior, and other data. This allows companies to efficiently respond to changing market conditions and possibly even improve profitability.

But the customers’ perspective is also important. We’ve all been frustrated when trying to book a flight, hotel room, or concert ticket, when we pause for a few minutes only to go back to the booking and see the price has increased. As customers, we make judgments about whether it is fair.

The researchers found that frequent price changes, different prices for different customers, and uncertainty about the information used to set prices can undermine trust. Managers were interviewed as part of the study, and they considered fairness and reputational damage to be major concerns. As pricing executive Mark Billige observed, customers are often less concerned about whether a price is simply high or low than whether it is higher than someone else’s or higher than it was yesterday.

The Oasis ticket sale saga illustrates why transparency can play a crucial role in customer satisfaction. Even if a pricing system is not algorithmically changing prices in real time, consumers may still believe that unexplained price changes are evidence that it is. Clear communication therefore becomes part of the pricing strategy itself.

The algorithm isn't supposed to replace the manager

To conduct the study, the researchers interviewed five pricing executives, surveyed 71 pricing managers, and conducted a case study involving 225 gift and memorabilia stores in museums, aquariums, and zoos across the United States and Canada.

The investigations revealed that managers who were reluctant to adopt pricing algorithms felt some reticence, not because they couldn’t see the benefits, but because they didn’t trust the ‘black box’ nature of the algorithm. They were concerned about the lack of transparency—how would they know the methods the algorithm used to determine pricing? Would it be fair? They also expressed discomfort with the lack of managerial control over pricing, and the potential for negative customer reactions.

This is why the researchers state the importance of human oversight. As Kevin Mitchell, President of the Professional Pricing Society, put it: “Sometimes people feel that they’re losing a little bit of control over their product, which might, from a career perspective, be their baby.” He also stressed the importance of oversight when pricing decisions are especially important to a company.

In the past, stores would update prices manually, which was labor-intensive and costly. This limited the number of price changes they could roll out. Then, electronic shelf labels were developed, allowing prices to be updated more frequently. But store managers still provided human oversight, governing the number of changes and the maximum and minimum price limits. In other words, automation did not mean removing people from the process; it meant giving them a different role in governing it.

As Billige says: “Someone has to own the pricing decision in the company.”

What happens when everyone's algorithm starts watching everyone else's?

There is a rising concern about how businesses could share algorithmic pricing information to keep prices as high as possible and reduce competition. So-called ‘algorithmic collusion’ is a regulatory concern, but the researchers found that empirical evidence for it is limited, and significant tacit collusion hasn’t been established across markets.

The pricing executives interviewed had different concerns. They felt that algorithms could intensify competition and trigger price wars. Bertini and his peers therefore caution against assuming that algorithms automatically increase prices. Their evidence suggests managers expect them to intensify competition and potentially lower prices.

That being said, there have been high-profile cases involving concerns about the anticompetitive use of pricing software. The company RealPage provides software to the rental housing industry in the United States. It was revealed that the software had features to limit rental price decreases and align pricing among competitors. The Department of Justice reached a proposed settlement with RealPage in 2025 requiring changes to its software as well as restrictions on the sharing and use of competitively sensitive information.

Regulators are cautious globally. Both the UK’s Competition and Markets Authority (CMA) and Spain’s Comisión Nacional de los Mercados y la Competencia (CNMC) have warned that algorithmic pricing could facilitate coordination between competitors to keep prices elevated.

What does your data say about what you will pay?

Another consideration is whether algorithms have access to personal data to tailor pricing to individuals. Personal data privacy is a sensitive issue for customers. Personalized pricing could improve efficiency and allow businesses to serve customers who would otherwise be priced out, but it also highlights potential issues about privacy, discrimination, and fairness.

This practice isn’t just theoretical. In 2025, the US Federal Trade Commission reported that companies were using personal data—including location, browsing and shopping history, and other behavioral information—to help set individualized prices. In Europe, consumer authorities have also scrutinized automated personalized discounts, including practices used by Tinder.

Companies are using algorithmic pricing. The decision for regulators is how they should be used. The researchers advocate for more studies on how transparency affects trust, how algorithms influence competition and consumer welfare, and how businesses can build effective governance and oversight into automated pricing systems.