On August 23, 2024, the Department of Justice (DOJ) sued real estate software company RealPage alleging the company’s software reduces competition between landlords, resulting in inflated rents and less favorable lease terms for renters. Specifically, the DOJ alleges that RealPage requires subscribing landlords to share their nonpublic pricing and occupancy information with RealPage, then RealPage uses the data to recommend prices for landlords competing in the same geographic areas. The DOJ also alleges that by using landlords’ nonpublic data in this way, RealPage thwarts competition from rival software companies that rely on public data, thereby monopolizing the market for such pricing software. In an environment where algorithmic pricing tools are becoming ubiquitous across a range of industries and under attack by numerous stakeholders, the DOJ’s lawsuit is one to watch.

The DOJ’s suit adds to a number of antitrust cases targeting algorithmic pricing tools. Its complaint and early decisions in the private cases provide valuable insights into features receiving the most antitrust attention. Importantly, these cases are in the early stages, and the defendants have denied any liability. This alert does not seek to predict the success of those suits, but to report on the issues raised in these cases.

Pricing recommendations

Significantly, the DOJ and the courts are not condemning the use of algorithms to provide pricing recommendations. In its complaint, the DOJ actually endorses one RealPage pricing tool that recommends prices based on public data, noting that this tool does not share “the same competitive defects” as RealPage’s two other pricing tools. Further, at least one court has dismissed a suit targeting software used to make pricing recommendations on the basis that the tool does not use nonpublic data. So far, the DOJ and the courts appear to be more focused on the nature of the underlying data and additional features and conduct surrounding the use of these tools than on the use of algorithms to recommend prices.

Nonpublic, competitively sensitive subscriber data

As noted above, pricing tools that rely on competitors’ nonpublic, competitively sensitive data to generate pricing recommendations are drawing more antitrust attention than tools that rely on publicly available data. Companies using nonpublic data may want to consider measures aimed at reducing the risk of antitrust attention, and should consult antitrust counsel for specific suggestions.

Delegated pricing and other ‘compliance’ features

The DOJ’s complaint spills considerable ink on RealPage’s “auto accept” and other “compliance” measures allegedly used to “outsource [landlords’] pricing function” and “align pricing processes, strategies, and pricing responses.”¹ The DOJ has alleged that such features can reduce independent decision-making between competing landlords. Companies using similar features may want to consider measures aimed at reducing the risk of antitrust attention, and should consult antitrust counsel for specific suggestions.

Procompetitive benefits of algorithmic pricing tools

While algorithmic pricing tools can give rise to antitrust risks, they also are increasingly common, and they can generate significant user and consumer benefits without violating antitrust laws. For example, such tools can efficiently evaluate varied and disjointed data to match individual supply and demand, increasing occupancy rates and lowering prices as often as they may increase them. Where such efficiencies are the driver, companies may want to consider memorializing this goal in marketing materials and internal business documents to be best positioned to defend and differentiate their model.

Do not use algorithmic pricing tools to fix prices

Importantly, the DOJ stops short of alleging that competing landlords use RealPage to fix their prices. Any use of algorithmic pricing tools to fix prices between competitors would raise significant risks. Agreements among competitors to fix prices are generally construed as “per se” illegal under the antitrust laws and may give rise to both civil and criminal liability. For example, in 2015, the DOJ brought a criminal action against online sellers of posters, alleging those sellers agreed to adopt specific pricing algorithms to coordinate pricing changes. The DOJ condemned the conduct as “per se” illegal price fixing. In contrast, the DOJ’s “information exchange” theory in the RealPage case is subject to review under the antitrust “rule of reason” standard, which will allow RealPage to introduce evidence of the software’s benefits and require the DOJ to show that any harm to competition outweighs these benefits in relevant antitrust markets – typically a high hurdle for plaintiffs.

Legislative efforts

Lawmakers at the federal, state and local levels also are pursuing legislation that would ban certain pricing tools, with San Francisco poised to become the first, but possibly not the last, city to ban algorithmic software used to recommend rents. And the week before the suit was filed, Vice President Kamala Harris publicly committed to take on pricing tools in the housing industry if elected president, stating “some corporate landlords collude with each other to set artificially high rental prices, often using algorithms and price-fixing software to do it. It’s anticompetitive, and it drives up costs. I will fight for a law that cracks down on these practices.”

DOJ’s suit against RealPage

RealPage offers three revenue management tools: YieldStar, AI Revenue Management (AIRM), and Lease Rent Options (LRO). The DOJ’s complaint targets YieldStar and AIRM, alleging that subscribers “agree[] to share detailed data with RealPage that are private, updated nightly, and granular.”² According to the DOJ, subscribers provide lease transactional data for every unit including “effective rent (rent net of discounts), rent discounts, rent term, and lease status; unit characteristics such as layout and amenities;” and information on expected lease expiration and future occupancy. The DOJ alleges that AIRM and YieldStar use competitors’ nonpublic, transactional data to recommend prices for individual units, and that AIRM also uses this data to train its models.

In contrast, RealPage’s third pricing tool, LRO, relies primarily on landlords to manually input data on competitors “that they have obtained from public websites.”³ Because “LRO does not rely on the type and quantity of nonpublic, transactional data pulled from competitors’ property management software or obtained from contacting competing landlords,” the DOJ characterizes LRO as a “less restrictive alternative” that does not share “the same competitive defects as AIRM and YieldStar.”⁴

The DOJ further alleges that RealPage employs mechanisms to increase landlords’ compliance with its pricing recommendations, encourage price increases, and otherwise limit competition between landlords. For example, according to the DOJ, RealPage:

• Promotes use of the software’s “auto accept” feature, which effectively delegates pricing authority to RealPage’s algorithms within certain parameters.
• Makes it easy for landlords to bulk accept pricing recommendations (and hard to override the recommended price by imposing administrative burdens).
• Deploys “pricing advisors” to escalate manual overrides of a recommended price to the landlord’s regional manager.
• Imposes a price floor that prevents the software from recommending a price that falls below a minimum market rent.
• Activates a “revenue protection mode” feature in low-demand periods to encourage landlords to limit available inventory to maximize price.
• Discourages landlords from offering discounts or other concessions to reduce negotiations with renters and maintain pricing.⁵

The DOJ contends that as a result of these mechanisms, competing landlords “effectively agree to outsource their pricing function” thereby “aligning users’ pricing processes, strategies, and pricing responses.”⁶

Private plaintiff suits

Private plaintiffs also have initiated a number of pricing algorithm cases spanning multiple industries. Although it is still early, decisions on motions to dismiss in a few of these cases – including in the private challenge to RealPage – provide some guidance.

In In re RealPage, Inc., Rental Software Antitrust Litig., the plaintiffs sued RealPage and its subscribers, alleging a conspiracy to inflate prices in multifamily and student housing. In December 2023, a Tennessee district court found that the plaintiffs had sufficiently alleged a horizontal agreement, based on “the simple undisputed fact that each [] Client Defendant provided RealPage its proprietary commercial data, knowing that RealPage would require the same from its horizontal competitors and use all of that data to recommend rental prices to its competitors.”⁷ But the court rejected the plaintiffs’ per se claim, because the “[p]laintiffs have not alleged any direct agreement or communication” and, since the defendants often overrode pricing recommendations, the court “[could not] find that” the plaintiffs “have alleged an absolute delegation of their price-setting to RealPage.”⁸

In Gibson v. Cendyn Group, the plaintiffs alleged Cendyn’s Rainmaker software, a pricing tool used in the hotel industry, was being used to “artificially inflate prices” for hotel rooms on the Las Vegas strip. Despite alleged similarities between Rainmaker and RealPage’s AIRM and YieldStar, the court dismissed the case with prejudice relying on one key distinction: “this case does not involve allegations of competitors pooling their confidential or proprietary information in the dataset that the pertinent algorithm runs on, while [the private RealPage] case did.”⁹

In Cornish-Adebiyi v. Caesars Entertainment, a New Jersey district court is considering the defendants’ motion to dismiss a price fixing case against Cendyn and hotel operators in Atlantic City that use the same Rainmaker software as in Gibson. Notably, in contrast to Gibson, Cornish includes allegations that Rainmaker’s algorithm relies on nonpublic pricing and occupancy data provided by subscribers who overwhelmingly adopt Rainmaker’s pricing recommendations.

What’s next

The RealPage litigation is likely to shed light on how the DOJ will seek to apply antitrust to new algorithm-powered technology – and shape the developing case law applying the Sherman Act to algorithmic pricing tools.

Companies offering and using these tools are well advised to engage antitrust counsel and consider the benefits and potential risks of such products, as well as whether appropriate safeguards are in place to mitigate potential risk. There are myriad potential options for companies who create or use these tools to reduce potential antitrust scrutiny. But each potential mitigation should be bespoke – designed for the particular tool and client.

Notes

1. Compl. ¶¶ 6, 237.
2. Id. ¶ 18.
3. Id. ¶58.
4. Id. ¶153.
5. Id. ¶¶ 65-70, 133, 136-37, 143-46.
6. Id. ¶¶ 6, 237.
7. In re RealPage, Inc., Rental Software Antitrust Litig. (No. II), 2023 WL 9004806 at *15.
8. Id. at *23.
9. Gibson v. Cendyn Grp., LLC, No. 2:23-CV-00140-MMD-DJA, 2024 WL 2060260, at *4 (D. Nev. May 8, 2024).