STR (Short Term Rentals) - How To Determine Occupancy Rates

[Daniel Beckius]

Here's the path I use to determine occupancy and rental rates for an STR (Short Term Rental) in any given market.

1. Log Into Airbnb & Vrbo Applications

2. Search the areas you're interested in buying in.

3. When you're searching, do NOT select a check in and check out date.

4. Select the properties that are the most similar to the style, size, bed, & bath count you're looking for.

5. Select the calendar for each property.  The calendar will show when there is an open date and when there is a booking for each month.

6. Divide the amount of booked days by the amount of days in the month and you'll have the occupancy rate (please note: for the most accuracy you'll have to visit each listing numerous times throughout the month considering there are cancelled bookings and last minute bookings.  Also, doing this over an extended period of time through the season changes)

7. 

[Bruce Woodruff]

Good info for all those newbies who come on here asking that question. My belief is that real-world research like this is far more accurate than AirDna etc....

[James Carlson]

Interesting post, and I used to do it this way with our clients, but AirDNA is just so much simpler. And for markets where there are a lot of Airbnb properties and a lot of data -- like Denver and Colorado Springs, for instance -- AirDNA's estimates are pretty accurate for both occupancy and revenues. The searching-through-Airbnb method, as you noted, requires seeing it multiple times at various points throughout the year to get a more accurate estimate. If you want to make an offer to buy a home for a short-term rental, you need quick data in order to make an offer in a competitive market. 

The one downside, of course, most of AirDNA's tools are not free. But really the Rentalizer is the only tool that's super important for estimate occupancy and revenue, and I believe that is still free to non-subscribers. 

Just my two cents.

[Patrick Farley]

Thanks for the info.

[Daniel Beckius]

I appreciate that James!

I only used AirDNA for the trial period a few years ago and at that time it wasn't that accurate, but if the data has become more reliable than it was, I'm all for it.  My only challenge to using these technologies is from my experience they aren't as accurate as if you or I were to do it "the old fashioned way".  Zestimates, Rentometer, Avm etc. still don't always have that reliable of data.  But if you're in a pinch why not put it into an auto estimator!

IMO as long as you see comparable properties getting high occupancy you'll be able to run the same numbers if not better... Assuming you do it right!

[Cole Britting]

@Daniel Beckius Really great post here with some super good info for an aspiring STR investor like me looking to get accurate analysis. Thanks!

[Daniel Beckius]

@Cole Britting I appreciate the complement!  I'm sure you're going to crush it! 

[Dan Thomas]

@Daniel Beckius

Good estimate for occupancy rate here. A couple added things to consider. Some hosts add prep time on either end of a booking so you are potentially adding 1.5 days per stay of inflated occupancy. Also in strong tourist towns, or perhaps really anywhere, hosts may stay in their own properties periodically throughout the yr also inflating occupancy. Hosts will also block out maintenance days, another inflation to occupancy rate. I may be wrong but I dont think airdna or any tool that I am aware of can determine real occupancy. I suspect they automate the formula you use?

[James Carlson]

@Dan Thomas

Good notes on the "buffer" around each booking and the potential that hosts are blocking off dates. Again, I'd say for most Airbnb investors, you need data quick to make quick decisions, and while I think the above strategy can get you close to accurate data, it also is time consuming when a tight competitive market requires quick action.

I used to be a lot more skeptical of AirDNA, but I've run the numbers on several of our Denver and Colorado Springs STR clients. What AirDNA projected and what they're making from their short-term rental is very close.

Also, I used to wonder about "booked" versus "blocked" dates, but they say that they can differentiate between the two. They have partnerships with these platforms, so they're getting that data from them. (You can read about their data scraping here. They talk about this point throughout the page.)

I sound like I'm schilling for AirDNA. I don't mean to, but because of my own analysis on our clients' Airbnb properties and from conversations I've had with reps in the company, I think they do a good job, at least in markets with enough data points to legitimize their estimates. 

[Daniel Beckius]

I should have rethought the subject line...  "free but old school way to determine occupancy rates"

I use Airdna just for the overview and I have clients that pay, but when doing market research they still look at every competitor photo, every amenity, home features, reviews, and even the hosts profile before investing in a market, neighborhood, or community.  So, I haven't run into an instance where we've needed to make a quick decision before having already done the due diligence.

I used Airdna 2017-2018, and at that time their customer service was terrible, there was missing data points, and didn't pull all of the competitors which is why I stick with the tactic I posted and my clients always end up in the 90th percentile of competitors.

Regardless, I agree Airdna is worth the investment even for the base subscription because of all it has to offer...  Also, after hearing @James Carlson it appears that is has become far more reliable.

But I wouldn't 100% trust an analytical tool until I'm in the metaverse. 

[Bruce Woodruff]

Originally posted by @Daniel Beckius:

But I wouldn't 100% trust an analytical tool until I'm in the metaverse. 

Yep. Algorithms vs an analytical human brain....hmmmm, let's see......