Over the past few years, we've seen multifamily revenue management software come under increased legal scrutiny.
Proposed legislation in markets like New York and California have raised important questions for owners and operators evaluating how rental prices are set, what data is being used, and where legal risk may exist. Similar legislative efforts are now gaining traction in other cities and states across the country.
To help clarify what’s actually happening, what regulators are trying to solve, and how operators should think about revenue management moving forward, I recently sat down with RentVision’s Revenue Management Product Advisor, Brooke Seifker, for an open discussion on the topic—which you can watch below.
Here’s how I see the big picture.
The main reason it’s come up the last couple of years is the large lawsuit from the Department of Justice against one of the major revenue management providers and a number of the large landlords that use it.
Because that’s made the news and become scrutinized, a number of smaller legislative bodies are enacting laws at the state or city level on various aspects of revenue management. There’s a lot of scrutiny around data sharing and whether that’s leading to price collusion, which is illegal.
What we’re seeing as of late is that while nobody is technically admitting fault in their settlements, they are all changing their practices.
That’s triggering obvious questions and demand for alternative options that minimize legal liability for landlords, and it’s quite the buzz.
I’d put regulators into two camps.
In one camp, you’ve got effective regulators trying to eliminate price collusion—and that’s a good thing. That needs to be eliminated.
In the other camp, you have some regulators who really want the government to control prices, and that’s going to have some negative unintended consequences on renters multiple years from now.
The first group, which is trying to eliminate price collusion, is really trying to eliminate and prevent private pooled data.
Think about it this way. If one individual controlled all the apartments in a metro, they’d essentially be able to raise all the prices at one time. Well, in some instances, software is controlling competing apartment prices and having those communities look at each other’s prices to determine what their prices should be.
If the software moves prices up in Apartment Community A and Apartment Community B uses A’s prices, it moves up. And if A then uses B’s prices, it moves up again. You get this circular dependency where prices just keep going up.
Some landlords feel like they’re off the hook because it’s the software doing it, not them—but that doesn’t eliminate their liability.
The other group of regulators wants to control how much rent prices can go up or down. I think that’s unfortunate.
Often that slows development of new properties, so residents have fewer choices in the areas they want to live. You end up with housing shortages, landlocked apartments, and not enough supply being built.
Then you see tenants subleasing apartments because they can lease them for more money due to rent control.
Those consequences usually show up two to five years after the policies are implemented.
No—not entirely.
But the data needs to be first-party data. Your occupancy. Your leasing velocity. Your renewal history. Your seasonality. Not your neighbors'.
Pricing done the right way really does benefit everybody. Pricing should go up where demand is higher and go down where it’s softer to incentivize developers to build apartments where they should build them.
When you get into price controls, you’re essentially banning either revenue management or certain aspects of it. That often feels good in the short term for renters, but not so much in the long term.
A little bit of history here is fascinating.
We’ve been doing revenue management long before any of the latest lawsuits and settlements, and we’ve never believed in using competitor data—for multiple reasons.
This was always a huge dividing point for us. It probably caused more people to not buy our solution than anything else, because they wanted to use competitor market data.
Now that tide is turning in a huge way.
One obvious reason we didn’t want to use competitor data is price collusion and lawsuit risk—which is why these lawsuits are happening. Another issue is circular dependencies that don’t always deliver good outcomes.
Why follow prices down on a property that has a bad leasing agent? Or if you have a bad leasing agent, why follow prices up? You end up with more vacancies.
But the other reason is we think there’s actually better data out there.
Ten to fifteen years ago, when I was looking at web data, I realized I could see which apartments were in demand, which ones were going to rent, and which ones were priced incorrectly. People are visiting websites weeks before they call the property, tour, apply, and move in.
That’s the earliest indicator of demand, and it’s property-specific. It shows unique seasonality.
From there, we built transparency into the software. Here are all the reasons the price went up. Here are all the reasons it went down.
Another reason it’s foolish to follow competitor prices is that your goals might be completely different. Your competitor might want high occupancy and low vacancy. You might be trying to sell your property in a year and want to maximize gross potential rent.
Those are completely different goals, and you should have completely different rental rates as a result.
The first thing is to look at where the data comes from.
If the data is coming from other properties, you’re definitely getting into a gray zone.
If it’s your data, it’s superior and keeps you above board.
The second thing is how predictive that data is.
I often get asked whether we look at employment data. The government puts that data out and then revises it months later. It’s lagging and often inaccurate—it’s some of the worst data you could use.
So the question should be: what are the data sources, and how predictive are they?
The last thing I’d encourage people to ask is whether the revenue management practices make sense for multifamily.
A lot of legacy systems were built for hotels or airlines, where supply and demand changes daily. In multifamily, demand is seasonal. The biggest swing might be the start of the school year, and that doesn’t even compare to airline demand changes.
You want a system that doesn’t upset marketing and leasing or add friction for multifamily properties.
Regulators tend to follow what’s in the news.
Whenever something becomes a headline, it turns into a hot issue and regulators pounce on it. That’s what we’re seeing now with multifamily revenue management.
A simple example: a senator recently posted about people being “ripped off” because the penny was eliminated and there wasn’t clear guidance on rounding. It’s not a big issue, but it was in the news—so legislators talked about it.
What we’re dealing with in multifamily is a much bigger issue. And the approach is very simple.
Do what is morally right.
Treat people the right way. Make sure your algorithms and rent-setting practices are above board. Don’t use other people’s rent data—either directly or through software.
Use your own supply and demand data, or software that does.
You can’t avoid receiving a lawsuit, but you can avoid losing one by doing the right thing.
That’s why we built RentVision Revenue Management the way we did—long before these lawsuits and long before legislative bodies became hyperactive in this area. We wanted to do things the right way without sacrificing performance, and actually use data that’s more predictive.