The Problem with Multifamily Rental Pricing

As every real estate professional knows, when an appraiser determines the market value of a single-family home, they look at recently sold comps. In standard markets with sufficient sales volume, they look at closing in the last 3-6 months. In lower volume markets, they sometimes go back 12 months or more. They may analyze asking prices too, particularly in rapidly changing markets, but closed transactions are the gold standard.

Why? Because sold comps reflect actual market transactions, which provide concrete evidence of what buyers are willing to pay for a property. In contrast, asking prices only represent what sellers hope to obtain. This is true in the sale of multifamily properties too - you'd never see an appraiser determine the market value of a single-family home or multifamily property solely based on asking/list prices.

So why in the world do investors, appraisers, brokers and property managers analyze market rents for multifamily units based almost entirely on asking rents at competing properties?

Let's look at property managers and multifamily acquisitions teams in particular. These groups have to either set market rents on a weekly basis, or they need to get really granular on analyzing market rents to ensure they make a good investment - both of which require access to up-to-date rental market data and a oftentimes a substantial time commitment to structure and manually analyze it. The process for getting this data usually involves logging into CoStar, Yardi, RealPage, or countless other systems and looking at their market rent data. Then they almost invariably say "I'm still going to the property website and listing sites, and I'm still calling the property manager to get rents and concessions."

It makes sense, because significant value could be created or destroyed based on their market analyses. It also makes no sense at all, because they are only collecting asking rents... only the owner or manager of the property knows where leases were actually signed.

Can you imagine an appraiser sending you a report with a cover letter saying "Since it was too hard to get closed transaction data, we just looked at listing prices for similar properties last Thursday when we put together the report. Here's our valuation, it's accurate, trust us."

Yet this is what countless real estate professionals are doing in multifamily every day. Even companies who aggregate listing data are typically only surveying rents monthly or weekly, and they're only capturing asking rents.

Here's why this is a problem:

If you surveyed on 7/7, the market rent would be $2,382, right? Then on 7/13, less than a week later, it miraculously jumps to $2,536. Another week later and it's $2,473... so what is the REAL market rent?

The constant fluctuations of revenue management systems make this difficult to figure out, but there is a way.

HelloData's approach is to capture the last price before a unit is taken off the market, then subtract the dollar value of any concessions that were present at that time to determine the effective rent. In comparing our data with several clients' rent rolls, we've found that the last listed price we pull from property websites and listing sites is typically within $5-10 of the actual leases signed by tenants. That's the closest you can get without owning the property! What we're essentially doing is finding the closing price of each unit, which again, is what everyone should do, and would probably be doing, if they could survey every property website in their comp set, every day.

When we combine this closing price with algorithms that extract the dollar value of concessions from advertised specials using AI, we can consistently determine the effective rents for properties across the country, all without ever picking up a phone.

To learn more about how property managers and acquisitions teams across the country are saving time and maximizing revenue with HelloData.ai, schedule a demo with our team today!

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HelloData.ai computes the latest effective rent for you using our own Large Language Model, learn more how we are using it to find the best rent comps: Rent Comps