AirBnB Calculator Tool

[Matt Cupp]

Has anyone identified a nice methodology of doing an AirBnB/VRBO analysis on a property?

[David Bergmann]

I'll share what I look at when I'm doing an analysis.  Like any business, you want to make sure you have a profit, which is the net of Revenue minus Expenses.  Revenue for short term rentals is more variable, so that is really the trickiest part of the analysis.  Expenses are more straightforward, so I'll start with that.  

Expenses:

• Real estate cost - Financing, HOA (if applicable), insurance, taxes, maintenance, other capital expenditures
• Operational expenses - Utilities, cable, landscaping, pest/termite, consumables, channel manager/pricing software, linen & other damages.
• Furniture / Upfront Cost - When I run my analysis, I always consider the cost to furnish the place as well, since that can be a pretty large upfront investment. For analysis purposes, I spread that cost over 3 years (36 months). So if it cost $8500 to furnish, I would show another expense line of $236 dollars for furnishings and ensure it cash flows with that in the numbers. This way you are essentially allowing yourself to be profitable even after buying new furniture every 3 years, although the lifespan of most furnishings should be much longer.
• Management Expense - I think a best practice is to include this in your numbers even if you plan to self manage. Justification here is you will be putting in time to manage yourself or paying someone to do this. Either way, want to make sure the numbers allow a margin for this. Your market will determine what you want to use for this value, but I've used 20%.

Revenue
For revenue projections, ideally you can triangulate this across 3 key areas, but sometimes you'll have to rely on only 2. I wouldn't personally make a decision on just one of these data points:

• Market Data (PriceLabs Market Dashboard, AirDNA, etc.) - this can usually give you average nightly rates, occupancy & revenue for an average of properties in a certain area with different bedroom counts. Typically, you'll also get a distribution that represents the percentile (25%, 50%, 75%) of the occupancy and rates. The average numbers tend to be low relative to what an experienced owner or property manager can do who knows how to optimize a listing. I tend to use the market data more for occupancy, rather than price per night, and will peg that to the 50% - 75%, or an average of the two depending on how conservative you'd like your numbers. For instance, in my market the 75th percentile occupancy is around 83%, and the 50th percentile is around 63%, so it'd probably use 73% in my analysis.

• Direct Competition (AirBNB, VRBO) - See Michael/Luke's message about ENEMY method. I tend to rely more on this to get an honest idea of the competition and how they are pricing their listings per night. You may also want to consider breaking out the weekday & weekend pricing here. Every market is different, but in my market I've observed from competitors and market data that Friday & Saturdays carry a 8-10% premium over weekdays (Thursdays carry a 4-5% premium).
• Internal Data / Personal Experience - Ideally you have another property in your portfolio that you can look at that is similar and can pull in that experience to validate your expectations. Even if it's not a perfectly comparable property, you may be able to use that experience to determine if you are performing at the 50th, 75th, or even 90th percentile. Then when you are using your market data you can develop an expectation that is based on your own capabilities.

Hope this helps!  Let me know if any questions.