Washington DC Airbnb & VRBO Market Analysis w/ AirDNA

I recently purchased access to the short-term rental market data in Washington, DC from AirDNA. Below is a summary of my learnings.

Research Data

Looking at the “Research” tab, AirDNA is ranking Washington DC as “B” for an overall short-term rental market grade.

Rental Channels: Looks like most of the short-term rental listings in Washington DC are on Airbnb. Only 7% of the listings are on VRBO only, which is lower than the average numbers I’ve personally seen in other locations.

Rental Growth is trending downwards for the past two years, which means the number of listings is decreasing (less competition). On this page AirDNA doesn’t have the option to allow me to filter these growth numbers from the number of bedrooms or occupancy but they do on the occupancy data page.

Common amenities list for Washington DC short-term rentals is a good list to know what you’d need to provide at your own property if you wanted to stay competitive. Looks like Cable TV is an amenity that hosts are not offering. Maybe a good cost-saving point. Hot Tubs are rare so maybe a good competitive advantage. Obviously, you can make the opposite claim about Cable vs Hot Tub but based on our own hosting experience I’m assuming hot tubs are more in demand than cable TV.

Rental activity: For Airbnb to consider a listing full-time, the rental has to be available for at least 181 days in the past year (not a full year). That said, only 33% of Washington DC listings are full-time.

That makes sense since Washington DC has a rule that limits hosts to 90 days of hosting a year along with other restrictions and some exemptions.

Rental Settings: it is interesting to me that most hosts have a “strict” cancellation policy. In our experience, guests rarely cancel their reservations, and those who do have good reason to. Having a flexible cancellation policy has worked for us. Obviously, it is not a one-size fit all.

Map View: I use the map view on the research page to filter out the location of property types that I’m interested in. For example, I was interested in finding out where most Airbnb listings of 3-bedroom size are located in the city.

Next, I like to filter a bit further so I go to the “Occupancy” page in AirDNA and select the below filter.

Filtered Occupancy Data: You can see the average occupancy rate has been going up a bit over the past two years which is probably explained more due to the ending of Covid restrictions than other conditions.

Filtered Active Listings: The number of active listings has been going down in the past few years but started to go back up in the past two quarters

Filtered Booking Demand: We can see demand is picking back up and that it's also seasonal. We can find out more about the seasonality of demand under the “Price” features of AirDNA.

The rates page has good average price information for the filtered types of properties. Not that you can see rate estimates between different property types; I’ve selected Upscale and Luxury. There are other options too. Also note that this data is based on 17 active listings and was updated 5 days ago.

Next, let's look at the “Revenue”” data published under the “Research” section. I find that the monthly revenue estimates are not as accurate as I like them to be. It makes sense since there are so many factors that go into the overall revenue mainly occupancy plus rate. Once you average these numbers it gives you exactly that, an average.

We’ve found that in the property we manage we can generate higher revenue than what AirDNA typically shows on their 90% percentile.

Price Data

Under the Price data section, the Smart Rates and Pacing pages are more targeted at hosts with active listings in that market and looking to analyze their prices against AirDNA’s recommendations. We currently don’t manage a listing in the Washington DC area so we’ll skip these two pages and go to the “Seasonality” page under the same section.

Looking at the Seasonality data, for properties of 2 to 3 bedrooms that accommodate 3 to 8 guests, the months of March, April, May (spring), June and July (summer), and the odd month of October seem to be the busier months of the year. We can use this data when we set the pricing strategy settings in tools like Pricelabs or Wheelhouse.

The booking lead time chart shows how far in advance guests usually book their stay given the filters we selected above. You can see reservations have longer lead times in the busier months than in the slower months.

The pie chart on the left shows more granular monthly data as well. We can compare January with May. Look at the difference between the number of guests who booked their stay 91+ days (3 months) in advance.

Invest Data

The Invest data pages are useful when making property investment decisions.

Rentalizer

The Rentalizer on AirDNA allows you to enter an address and get estimated monthly rental income projections. We’ll use the address for a property that is currently listed for sale on Zillow.

The data says this property can generate about $119k in revenue a year at an average daily rate of $376 with an 87% occupancy rate. Keep in mind that all costs are included in that amount too.

AirDNA is showing the rNet Operating Income at ~ $78K and a cap rate (dividing a property’s net operating income by its asset value) of 6.84%. Keep in mind a few important assumptions that you need to modify for more relevant estimates:

• 20% management fee to include all costs including furniture, cleaning, utilities, and insurance.
• You purchase the property in cash. There are no mortgage payments taken into account here.

This is a good starting point or addition to the rest of the real estate analysis that an investor completes on each property.

Top Properties

The Top Properties section shows the top properties in our selected location (Washington DC) and filters (2 to 3-bedroom single-family homes that accommodate 3 to 8 guests).

AirDNA calculates the revenue for comparison properties from the last 12 months based on their actual availability. If a listing was active only 30 days out of the year, the system calculates the annual income based on those 30 days. That’s not as accurate in my view because maintaining a high occupancy rate at your price point is one of the most important parts of running a short-term rental business.

So under the Top Properties section, I look at the listings that have a higher number of reviews and for the most part, ignore the data for the ones with the lower number of reviews.

Market Comparison

This section allows us to compare a few different neighborhoods or cities or states with each other. We’d have to have paid access to all of the locations that we want to compare in order to see all the data here.

I used zip codes from Georgetown, Capital Hill, and Navy Yard areas of DC to compare with each other. I also filtered the results for 2 to 3-bedroom listings that accommodate 3 to 8 guests.

Summary

The AirDNA short-term rental market data for Washington DC showed that the majority of listings are on Airbnb, with only 7% on VRBO. The number of rental listings has been decreasing over the past two years, reducing competition. Amenities such as hot tubs can give a competitive advantage, as they are rarely found in listings. Only 33% of listings are full-time, probably due to DC’s rule that limits hosting to 90 days a year. Interestingly, most hosts implement a “strict” cancellation policy. Occupancy rates have been rising, likely due to the lifting of Covid restrictions, while the number of active listings has been decreasing, though it started picking up in the past two quarters.

The AirDNA data also provided insights on the pricing strategy, with March to July and October being the busiest months, and hence should command higher prices. The “Rentalizer” feature predicts potential revenue for specific properties. Comparisons of different neighborhoods showed varied results, underlining the importance of location in short-term rental success.