The year is 1999 and you’re walking down the street sweating on a hot July day. You walk past a Coca-Cola vending machine and stop for a can of Coke, and you notice the price is higher than it was the other day.
What gives?
It turns out that in ‘99, certain Coca-Cola vending machines had temperature sensors that would increase the price of soda as the temperature outside rose. However, after much public backlash, Coco-Cola quickly removed these vending machines from the market.
Here, we have an early example of dynamic pricing using a very simple algorithm at work.
In Coca-Cola’s case, the issue wasn’t a legal one–it was a PR one. But with the rise of AI and more advanced technology, dynamic pricing has been outsourced to extremely smart and sophisticated algorithms, leading to breaches of antitrust laws and lawsuits around the country.
The controversy around dynamic pricing and algorithmic pricing models
So if Coca Cola wasn’t in violation of any legal regulations, when exactly do these algorithms become problematic?
In industries like real estate, companies have started using real-time dynamic pricing algorithms to determine rental prices based on multiple relevant factors, including competitor rates and other non-public data such as unit availability. While this isn’t inherently problematic, it becomes an issue when multiple real estate companies feed their rental prices into a single algorithm that, in turn, recommends inflated prices based on non-public competitor data.
This is a clear violation of antitrust laws.
The Sherman Act, one of three primary federal antitrust laws, prohibits both monopolistic practices and agreements between businesses that limit competition, such as price-fixing or market division. And while realtors aren’t directly sharing prices in person, they still violate the Act by feeding prices and other non-public data into a shared algorithm that then suggests rate increases across users. In these cases, the typical risk of losing customers to competitors who charge less is removed, which undermines competitive pricing entirely.
Are algorithmic pricing models inherently anti-competitive?
Algorithmic pricing models, in and of themselves, are not anti-competitive. However, concern about anti-competitive practices arise from the potential misuse of data through algorithms.
For example, a landlord might utilize software with an algorithmic pricing model for price optimization purposes. The algorithm may process real-time market data, such as customer data, business data, and broader market trends, to determine the best pricing strategy for rental prices. This is completely fair and just.
Similarly, algorithms can be employed based on supply and demand principles, much like how stock prices are determined. In such cases, algorithms simply automate processes based on predefined rules or market conditions, and they function within the bounds of fair competition.
However, issues arise when competitors in the same field pool their data into a single system. When a competitor uses this collective data to set prices across the market, it can result in anti-competitive behavior, leading to higher prices and reduced competition.
For example, RealPage, a property management software which recommends rental prices for 4.5 million housing units in the US, has been sued multiple times since 2022 for breaching The Sherman Act. The company was accused of allowing landlords to collude using the algorithmic model built into its software.
Is there any legislation regulating algorithmic pricing?
After the exposure of the RealPage case and the pervasiveness of AI’s role in dynamic pricing, Congress, the Department of Justice (DOJ), and the Federal Trade Commission (FTC) began paying closer attention to this growing issue.
Senator Amy Klobuchar has been a key player in establishing federal policies and regulations to monitor algorithmic pricing.
In November 2022, Senator Klobuchar, along with Senators Dick Durbin and Cory Booker, urged the DOJ to investigate any potential anticompetitive conduct affecting apartment rent rates.
The DOJ and FTC have also filed multiple statements of interest addressing the proper legal framework for algorithmic price-fixing claims. And in April, the DOJ’s Antitrust Division announced it would evaluate algorithmic information exchanges using the same criteria it applies to traditional, in-person exchanges of information.
Then, in 2023, Klobucher established the American Innovation and Choice Online Act, which aimed to boost online competition by restricting tech companies from misusing their power to undermine competition and consumer choice. Last year, this Act actually marked a milestone as the first digital competition bill to move forward in Congress since the inception of the internet, passing the Senate Judiciary Committee with a 16-6 vote.
Lastly, on February 2, 2024, Klobucher introduced yet another key regulation, the Preventing Algorithmic Collusion Act, to prevent companies from using algorithms to collude and increase prices. This act aims to modernize antitrust enforcement by specifically targeting algorithm-driven pricing models that manipulate competition, and it proposes new monitoring measures to catch early signs of price-fixing.
On a local level, we are beginning to see similar legislation. In September, the city of San Francisco completely banned algorithmic pricing in the rental house market to prevent collusion and stabilize rental prices, which have increased by 20% nationwide since 2020.
Class action cases against algorithmic pricing
In 2022, plaintiffs’ lawyers brought the first major suits against algorithmic pricing. The suits accused RealPage of allowing landlords to collude by using its property management software to exchange pricing data.
The lawsuit states that the software led to coordinated and anti-competitive actions that significantly drove up rental costs across the nation. The case was then merged into a multi-district litigation in Tennessee, and is still pending.
We are now seeing an emerging trend in antitrust litigation against RealPage, with additional lawsuits filed in both Las Vegas and Atlantic City, all alleging that the software’s algorithm drives up rental rates. On November 1, 2023, the District of Columbia Attorney General took similar action, filing a lawsuit against RealPage and several landlords in D.C.’s Superior Court for alleged violations of the D.C. Antitrust Act.
The RealPage cases plus the additional lawsuits pending against other property management software companies for similar violations highlights the magnitude of this issue. Hopefully, as local governments and federal bodies continue to put pressure on tech companies and landlords to avoid this practice, we’ll begin to see more transparent and competitive practices in real estate markets.
Moving forward: The future of litigating antitrust cases
As the focus on algorithmic pricing in rental markets intensifies, class action lawyers should prepare to navigate complex data-sharing practices and potential antitrust violations.
Key strategies include building a deep understanding of how pricing algorithms function within property management software to assess the extent of data pooling and identify collusive practices. Regularly consulting with data experts can aid in identifying hidden patterns of price-fixing or anti-competitive behavior, and monitoring updates in algorithmic regulations and engaging industry watchdogs can provide early insights into emerging cases.
Additionally, educating affected clients and potential plaintiffs about their rights under both federal and state antitrust laws will strengthen cases and support broader consumer protection goals.
Speak to one of our legal experts to build your next antitrust case
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