On March 2, 2026, the UK’s Competition and Markets Authority (CMA) announced a formal investigation into three of the world’s largest hotel operators: Hilton Worldwide Holdings, InterContinental Hotels Group (IHG), and Marriott International. The probe centers on allegations that these industry giants may have used a third-party data analytics platform to share competitively sensitive information, potentially stifling competition across the British hospitality sector.
At the heart of the investigation is CoStar Group Inc. and its subsidiary, STR (formerly Smith Travel Research). STR is a widely used benchmarking tool that provides hotel performance data, such as occupancy rates and average daily room rates.
While the CMA acknowledges that data analytics and algorithms can often benefit consumers by lowering costs and allowing for faster price adjustments, they become a legal liability when they serve as a “middleman” for collusion. The regulator is concerned that by sharing granular, real-time data through this platform, rival hotel chains reduced the “natural uncertainty” of the market. When competitors know exactly what their rivals are doing, they are less likely to fight for customers by lowering prices.
Together, these three chains operate nearly 650 hotels across the UK, spanning brands from budget-friendly Hampton by Hilton and Holiday Inn to luxury staples like Marriott and Kimpton.
The Impact on the Consumer: Why This Matters to YOUR Wallet
To the average traveler, a “data sharing investigation” might sound like a technicality for lawyers and economists. However, anti-competitive practices in the hotel industry have direct, tangible consequences for anyone booking a weekend getaway or a business trip.
First is “Sticky” prices and the end of discounts, in a healthy, competitive market, if a Marriott is half-empty, it should theoretically lower its prices to lure customers away from a nearby Hilton. However, if both hotels are using a shared data platform that signals their pricing strategies and occupancy levels in real-time, the incentive to “under-cut” the rival disappears. Instead of a “race to the bottom” on prices that benefits the consumer, prices become “sticky”—staying high across the board because no one wants to break the unspoken status quo.
Second is Artificial scarcity, data sharing allows hotels to coordinate even if unintentionally on how many rooms they release at certain price points. If data shows that all competitors are maintaining high rates despite medium occupancy, a hotel feels “safe” keeping its prices high rather than offering a “last-minute deal.” This creates an environment where the consumer feels prices are high everywhere, leading to a false sense of scarcity.
Third is reduced innovation and choice, when companies focus on “matching” each other through data points rather than “beating” each other through better service, the consumer loses. Competition drives hotels to offer better amenities, loyalty perks, or unique experiences to stand out. If the primary “competition” is happening via an algorithm, the drive to improve the physical guest experience may take a backseat to digital price-optimization.
Fourth is the “Algorithm Tax”, when hotels pay for expensive data analytics services to monitor their rivals, those costs are rarely absorbed by the corporation. Instead, they are often baked into the room rate. Consumers essentially pay a “tax” to fund the very software that prevents them from getting a better deal.
What Happens Next?
The CMA is currently in the evidence-gathering phase. If the regulator finds that the Hotel chains infringed on the Competition Act 1998, it could result in massive fines up to 10% of global turnover and legally mandated changes to how these companies use data.
As the hospitality industry increasingly relies on “Big Data” and AI to set prices, this investigation serves as a landmark warning: while technology can make businesses more efficient, it cannot be used as a digital smoke-screen for old-fashioned price fixing. For the UK traveler, the hope is that a return to “uncertainty” in the market will lead to more certain savings at checkout.