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The Complete Guide to Airbnb Data Analysis with AirDNA

airbnb data airdna alternatives competitors market research analysis str short term rentals best markets US vrbo

Table of Contents

Intro to Airbnb Data Analysis

I’ve been using the most popular Airbnb data tool, AirDNA, on and off since I left Airbnb in 2015. Recently, I dove back in to find the best short term rental markets in the USA for my next Airbnb investment.

This blog will be both a review and tutorial of AirDNA, an introduction to alternative Airbnb data tools when necessary, and a guide on rental market analysis in finding your own profitable property.

If you’re outside the USA, my AirDNA tutorial will be relevant because the STR data and dashboard presentation are identical for all countries. My last real estate investment was outside the USA in Colombia, with an ROI of 33% over the first two years.

If you’re new to the OptimizeMyBnb.com blog, I write different for a few reasons.

First, I am a real user, using my own money and months of my time getting to know the AirDNA tool before I publish anything.

Second, my reviews are fully comprehensive. That means everything you see within AirDNA will be discussed below, including the less popular but more valuable Airbnb analytics tool options.

Third, my AirDNA review will be brutally honest, which means I’ll be talking about the negatives just as much as the positives.

My hope is that by the end of this AirDNA review you’ll know whether or not you want to give your time (more important) and money to this Airbnb data tool.

airdna markets review calculator brutally honest

There are three modules once logged into AirDNA: Market Research, Revenue Calculator, and For Sale. I will be covering them in that order.

I am subscribed to the AirDNA Pro level for $85 monthly. Pro is the highest (sort of) access you can pay for. I’ll explain more about that when I talk about AirDNA pricing.

By the way, for those of you looking for an AirDNA free trial, it doesn’t exist. AirDNA discount coupons and promo codes also don’t exist. I asked for something for my readers. But, don’t worry, I’ve got a 50% discount to an AirDNA competitor below.

AirDNA Market Research Dashboard

When AirDNA changed ownership, one of the major updates brought to the platform was a focus on giving user’s access to more market data and reducing the cost. While that was accomplished (lower price/more market data), there are many nuances and much rental market data is still hidden even with the Pro subscription. More generalized data is not all that useful, but I’ll discuss this more in “How to use AirDNA?”

Once logged in, you’ll get a map of the entire world. There’s nothing to do here besides selecting a country. For this blog, I am choosing the United States of America.

You’ll notice that AirDNA has defined hundreds of markets and thousands of sub-markets. A sub-market is a neighborhood. It’s important to note that smaller markets often have no sub-markets identified, so the dashboard data will be pulled from the entire geographical area of the market (ie an entire county or city) rather than a neighborhood. This is an important distinction to be aware of and makes the data less reliable for these smaller markets.

On the screen above, you can sort these markets by one of four filters:

Market Score – An assigned score out of 100 given to a market based on investability, rental demand, revenue growth, seasonality, and regulation as defined by AirDNA. Unfortunately, my search for the details behind how this score is calculated yielded unsatisfactory results. I place no confidence in the number. I explain more in ‘How Accurate is AirDNA?’

Occupancy – As best I can tell, this is some kind of market average occupancy. This is a useless piece of data unless I am planning to be an average host expecting between 50-70% annual occupancy. There are large occupancy variances between rental size. A 1-bedroom may reach 95% for the best hosts, but given so much competition (ie supply), the profit margin is lower than a 3- or 4-bedroom with an occupancy of 75%.

Revenue Potential – Also seems to be a market average which makes it equally useless. In Market A with an AirDNA revenue potential of $50k there will be homes making $10k and probably $150k while in Market B with a revenue potential of $100k there will be homes making as little as $15k and possibly as much as $250k+. You should be able to see from this example that Market B isn’t necessarily better than Market A as long as you buy an STR for $101k annual revenue potential. You’ll learn later that 3-, 4-, and 5+ bedroom homes are generally going to be most profitable.

Key Point: A rental market should be analyzed by size home (number of bedrooms and bathrooms) as each has a unique supply and demand. A man with a family might rent a 3- or 4-bedroom STR on one trip, and rent a studio or 1-bedroom when he returns on a work trip. Two entirely different guest avatars.

Daily Rate – Again, a market average, but, unfortunately, AirDNA doesn’t tell us how it arrived at the number. Is it a true market average? What about if a home was only listed at high rates during the three-month busy season?

Let’s jump into Tulsa, Oklahoma, one market I’m looking at to invest in an STR due to a $2 billion theme park project called American Heartland to be completed in 2026. I examined Houston, Texas in a video as another potential inevitable market due to medical tourism.

By the way, I’m sharing all my vacation rental market research real-time in the forum and on live group calls with my Profitable Properties Program.

AirDNA Market Overview Dashboard

You probably already know that I’m not a fan of any of this data because it’s all market averages, which is not useful to serious Airbnb investors.

The good news is that each of these four metrics has its own module, which we will explore soon.

One thing to note here are the submarkets. Submarkets shown in the AirDNA dashboard can best be described as popular neighborhoods. They are smaller sections of the chosen market. In my newest book, Profitable Properties, I discuss my concept of micro-neighborhoods as the most important part of my vacation rental market analysis.

A micro-neighborhood is a very small part – next to a park, on the east side of a particular road, or even a specific street – of a neighborhood. In your search, you’ll want to get as detailed and specific as possible in finding the most profitable micro-neighborhood of your market. If you make a good vacation rental investment, the rest is easy.

Compare that with the many video consultations I’ve had with hosts who’ve made a bad rental investment. They are going through a lot of discomfort (and for many years to come) because they either did not take this part seriously, were led astray by faux Airbnb experts, or relied to heavily on faulty Airbnb data tools.

For the purposes of this AirDNA tutorial, we’ll stay in the market-level view of Tulsa because there is slightly more data to examine. Regardless, the metrics are the same if I selected a sub-market only with fewer listings.

AirDNA Market Performance Dashboard

Rental Market Details: Listings

Within your short term rental investment decision are two important metrics: supply and demand. You will need to know, as best you can, both. Supply is easier to get at and is represented by listings—the demand we will discuss with occupancy.

The first thing I notice is a discrepancy between the Total Active Listings (1,594) shown here and the 2,500 STR Listings shown in the Market Overview Dashboard. I will assume the data here is for the Total Active Listings. There are already plenty of assumptions you’ll have to make in the inventing process (ie potential errors) that I don’t want to add in any unnecessary ones so this is not ideal.

The Listings by Rental Channel, Lisitngs by Rental Size, Listings by Annual Availability, and Listing by Rental Type are fairly similar in any market.

The listing growth is interesting and our first piece of actionable data we can use. You’ll often hear from other hosts’ and Airbnb property managers how there are so many more listings this year than last. But this information by itself is useless. It’s just one of the two essential metrics. What if demand grew at twice the rate of listings? That would be a great thing. Demand is much harder to know but occupancy serves to help a lot in making some assumptions around demand.

Unfortunately, when we get down to the AirDNA occupancy metrics, the rental market statistics provided are too general. But, I have another Airbnb data tool that I want to introduce you to.

It’s one that I’ve used more consistently over the years and it’s called AllTheRoms Analytics. Below is just a peak at their dashboard, where they not only present listing growth (purple), but also occupancy (green) so you can visually see how the occupancy (ie demand) has moved in line with the listing growth (ie supply).

all the rooms analytics listings supply growth with occupancy 3 years

You can see that the listing growth has caused a slight decrease to market occupancy. As always, we’ll need to further dig into these numbers which we’ll do in the section on occupancy.

If you want to use AllTheRooms Analytics I was able to convince them to offer a 50% discount off their subscription price for one year to readers of my blog. You must use the code in caps OPTIMIZE50.

I like the short term rental statistics presented below:

airdna cancelation policy market average listings min stay

Most STR markets will have a similar distribution between cancellation policy and mininmu stay requirements, but when a market doesn’t, this is when the above becomes useful.

I was recently on a consultation call with an Airbnb host in a cleaner-dominated market (ie a market with fewer residents than STRs) who told me his minimum should not only be 7 nights but also with a check-in/out only on a Saturday.

I was like, wait, hold up….excuse me?!?

“Yeah, that’s just how everyone does it here.”

My draw dropped to the floor. Ok. So, let’s definitely not do that then becuase you’d be excluding the following FPGs (Future Potential Guests):

  • Anyone looking for a one, two, three, four, five, or six night reservation
  • Anyone who wants to check-in on a Sunday, Monday, Tuesday, Wednesday, Thursday, or Friday

Cleaner dominated markets are my worst nightmare because you’ll have to pay them more and often the service is worse. Your clenaer can be your greatest asset or your biggest time suck.

If you’re looking for a cleaner, I recommend using the app Turno and their Cleaner Marketplace.

To reiterate, if you notice a significantly uneven distribution on either of the above two metrics (min nights or cancellation policy), then you should think about servicing that gap in the market.

This tool seems cool! At least for some Airbnb market analysis as part of your all-important data gathering to finding your profitable property.

I tested this tool in a secret market I’m looking at. I decided on this secret, Undiscovered Market because it’s a smaller rental market and was curious if AirDNA can only match Airbnb property managers in larger markets (in Part 2: Vacation Rental Market Analysis in my book Profitable Properties, I discuss the differences between Dicovered and Undiscovered markets).

They matched me with three potential property mangers:

airdna recommended property managers by market connect

I have written up a detailed guide to help you decide whether you even need an vacation rental property manager, and if you decide that you do, how to choose one a good STR property manager.

Back to Tulsa. What’s interesting is that in the Tulsa market, the AirDNA tool provided me the following breakdown (below) of the largest Airbnb property managers with their size and average rating, but did not provide this information for the smaller, secret market above.

Here is what I see for Tulsa, Oklahoma:

If you have experience using the AirDNA recommended property managers tool, please share in the comments below. Thank you!

Airdna Market Details: Occupancy

When I got down to the AirDNA occupancy data, I realized that this tool is catering to non-techical Airbnb hosts. That’s not necessarily a bad thing.

These questions in the dropdown are cute. They’re even relevant. But, they’re providing general market data. Even with the filters above, which I’ve dedicated a section to in this AirDNA tutorial, we still don’t know exactly what’s included.

AirDNA has tried to answer the questions, in question format, that the majority (read: average) vacation rental investor might be wondering instead of providing detailed filtering options.

Non-techincal, average Airbnb host: What percentage of the month was occupied?

Techincal Airbnb host: What is the annual occupancy for the 90th percentile of listings?

The more detailed you make your questions, the more relevant your rental market analysis will be and the easier your life as an Airbnb host (not to mention more profitable!).

I’ve echoed that sentiment various times already and will do so many more times. There’s a marketing principle (it’s actually a persuasion principle) that says you have to expose a potential customer to something a annoyingly high amount of times before they start to recognize it. Same here. Be detailed. Be profitable. Be general. Pay me $200 to try and fix your short term rental investment problems. I don’t want your money to fix avoidable problems.

Let’s jump back over to AllTheRooms and see what they have for Tulsa market occupancy data.

alltherooms str analytics occupancy data top 90th percentile listings

AirDNA only shows you that general 46% number which is the market average occupancy. This answers the non-techincal Airbnb hosts, but is not only not relevant, but could lead us to a bad STR investment.

When I go into any vacation rental market, I know that I’ll be the top 10% of listings (or the 90th percentile as is represented by the dotted line above). For this category of hosts, the annual occupancy I can expect looks closer to 90%. That’s what I’m talking about!

My Airbnb, The Belmonte Penthouse, has an occupancy over the past two years of 94%. (and a rating of 4.99 if you don’t mind me indulging myself in some bragging. Hey! It was hard work and I’m proud of it!)

Below is a screenshot from AllTheRooms of the Medellín market occupancy data for entire home rentals, 4 bedrooms, in the very specific Provenza/Parque Lleras micro-neighborhood. The dotted line is the 90th percentile.

medellin top 90th percentile best 10% of airbnb hosts occupancy data all the rooms analytics

If you’re not keeping score..

AllTheRooms Analytics: 2

AirDNA: 0

The best Airbnb hosts, the ones who are following me, are technical or see the value in being technical. Don’t be scared if you’re not a technical host. With my guidance you will be. That’s becusaae I break down concepts into tiny pieces of relatable information.

If you wanted a bit more, I invite you to join my Profitable Propetie Program where you’ll get access to a forum of like minded hosts (one of the threads is dedicated to Vacation Rental Market Analysis), video explanations from me, and an organized syllabus to help you get to a technical Airbnb hosts making tons of money from your profitable short-term rental.

You can join at a lower subscription price, or purchase a lifetime membership which includes an array of bonus materials valued at nearly the cost of the program. Both memberships include access to the forum.

You can also post a comment below and I’ll respond there.

Market Details: Revenue

Good job, AirDNA! I’m seeing percentile ranges here which is very important for me to build out my short term rental investment analysis. A step in the right direction.

There is still one problem, though. I am going to ignore total revenue data in all data analytic tools becuase I’m going to calculate that myself with the following formula:

[365 days * 90th percentile annual occupancy] X [Average daily rate of 90th percentile]

The above formula would give me a specific, but estimated revenue for any listing. As I teach in my books and online course, you should create two revenue estimates, one conservative (ie worst case scenario) and one expected (never create an optimistic scenario). You want both of these estimates to be cautious to insure we’re not making a poor Airbnb investment.

I actually do this revenue analysis per listing bedroom size (see below). Here’s a sneak peak from the Profitable Properties Program. I won’t take your time in explaining the details here, but the most important thing to note is that I’m calculating my own revenue and comparing that to the average home price of the same size. You can see that for this undiscovered vacation rental market, we’d probably want to avoid a 3 bedroom home and focus on a 5 bedroom home.

This is because we have an extra $150k above the average 5-bedroom home value to work with. In other words, we can buy a nicer 5-bedroom home and earn a nicer return on investment.

how to decide what size home is best for an str investment atr data

Airdna Rental Market Details: Rates

airdna guide average daily rate metrics accurate

The AirDNA market details for daily rates is shown above. The other questions this module answers are:

What was the average daily rate?

What was the average daily rate by bedroom?

What was the average daily rate by day?

What was the average daily rate by price tier?

What are guest willing to pay for future days?

How much on average are hosts changing rates?

The last question is the most intriguing, but is only accessible with the Advanced subscription which we’ll talk about below in the Airdna pricing section.

I think it’s the most intriguing because I would love to know which markets are hosts not using dynamic pricing tools. I would enter these markets without much thought.

In fact, one of the heavily weighted factors if I’m going to buy an existing STR in any market is whether or not the host was using a dynamic pricing tool. I know if they were not, I can increase revenue by at least 25%, but sometimes double it. Or more.

That’s why I recently brought back my Revenue Management service. Pricing gives host the most trouble yet it has the most upside in terms of ROI.

It’s an extreme example, but the prior property mangers of The Belmonte Penthouse were charging $500 every day of the year. Their weekends got booked up easily and they were making about $45,000 annually (roughly 8 nights per month). Last year, I made $163,000 with the same property. The owner even sold me it as is, only taking a few things with him.

With the same exact property, I am making 4x from the prior management! This wasn’t all due to pricing, but I do attribute the majority to my pricing strategy.

And to think I was even considering hiring that Airbnb property manager because the prior host said they had a good experience with them! I would have missed out on $100k+ if I didn’t self-manage.

If you are looking for full-service property management, there is one company on this entire planet that I recommend: Midtown Stays/STR Riches. It’s run by a friend of mine and a super successful short term rental host and investor. Click here to learn more about them.

I have the best pricing strategy in the market. I know pricing is confusing for both new and experienced Airbnb hosts alike, but my strategy is also very simple. It’s a two-step strategy that needs reviewing only one per week. After you learn my strategy, each listing you manage will need an average of 30 seconds per week of pricing management.

Step One: Create booking targets with your listings booking lead time

Step Two: Add customizations, if needed.

You have a few options to learn more about my pricing strategy:

Read ‘Part 5: Pricing’ from my STR book Profitable Properties. There you’ll find the five common calendar occupancies and how to deal with each scenario.

Watch my YouTube playlist discussing my Airbnb pricing strategy. I feature PriceLabs here as they’re my only recommended pricing tool.

Join my Profitable Properties Program (many use the Q/A session to dive into pricing).

Book a private, one-on-one video consultation.

I have recently reintroduced my Revenue Management service which has been dormant for 4 years. This decision was made purely due to popular demand and consistent requests over the years.

Market Details: RevPar

What is RevPar? AirDNA says “RevPAR or Revenue Per Available Rental is calculated by dividing total revenue generated by the number of available properties in the market.”

In other words, this metric takes into account unbooked days, or occupancy. RevPar will always be lower than daily rates. The prior owners of The Belmonte Penthouse RevPar was $133 ($4,000 total monthly revenue made up from 8 weekend days at $500 per night/30 days)

My RevPar is $472 ($163,000 annual revenue / 345 available days). My daily rates range from $200 to $1,000+.

If you’re looking for an international short term rental investment, I am selling The Belmonte Penthouse to upscale to even large, more luxurious Airbnbs. The purchase would come with access to my team. Serious inquiries only. Asking $900k.

Regarding the RevPar for Houston as presented by AirDNA, it’s useless because..why? Pop quiz. It’s a general number and we need specifics to make the most profitable investment decision.

Be sure to read my section titled “How Accurate is AirDNA?” for a deeper discussion about numbers and why they’re all wrong. I was a Certified Public Accountant for the start of my career, including at Airbnb. I know numbers.

I do like the below chart, as it gives a nice presentation of demand/occupancy displayed ina fresh and new way I’ve not seen before. You can see that weekends are clearly a favorite. You may have already known that going into the market, but I still like this display. Plus, it shows you which months have less demand, so you can lower your rates early.

Caution: Regardless of a market having a high or low annual occupancy, the below presentation will always show light purple (low demand) and dark purple (high demand). In other words, it doesn’t show how likely these days are to get booked, only at what rates. The light purple will get booked at lower rates but may only be slightly less likely to get booked.

In other words, if the below AirDNA market data were for Medellin (with a yearly occupancy of 90%), then most of these dates would get booked, just at different rates. Weekends high. Weekdays low. I don’t want you to think that weekdays are unlikely to get booked and thus lower your pricing too much. However, if you follow my pricing strategy, this doesn’t matter as your weekly review would catch this booking trend early and allow for adjustment.

Key Dynamic Pricing Tip: When it comes to low demand days whether that’s low season or low days of the week, lower your prices a little more and a little sooner than the competition. One way we accomplish this is with a gradual discount of up to 50% through your booking lead time which is typically around 30 days. I talk more about that in my YouTube video dedicated to PriceLabs customizations. We also go over this pricing customization in my Profitable Properties Program.

AirDNA Market Filters

Rental Market Listing Filters

AirDNA provides many of the standard filters that any Airbnb analytics tool would provide plus some specific ones. I’ll discuss all of their STR market data filters in this section.

First, the standard filters:

  • Type of listing: entire place, private room, shared room
  • Type of rental: apartment, B&B, house, or unique
  • Bedrooms: from studio to 6+ bedrooms
  • Bathrooms: from 1 to 6+ bathrooms
  • Number of guests: from 1 to 10+ guests

Changing any of the filters will change the metrics shown in the dashboard. However, it will still show generalized information about whatever filter you’ve chosen.

For example, I’ve just filtered for Entire Place, 4-6+ bedrooms and bathrooms. The Airdna rental data updates, but I only see all the data for all 35 listings in this data set. As a technical Airbnb host, I know that within this data set there are winners and lowers…there are favorable geographical locations, etc. But I am restricted from this data making it less useful.

AirDNA says the average annual revenue is $107,100 for these filters. But I want to know the range. Some are likely making much less and others much more than $107,100. What if all those listings making the most in this data set all were 4 bedrooms? What if all those 4-bedroom rentals were in a specific location? You can see how tremendously important that information would be?

I could filter further by a pre-set neighborhood as defined by AirDNA, but many smaller markets (the Undiscovered Markets) have no sub-markets. Regardless, I prefer using AllTheRooms Airbnb analytics map feature so that the data shown reflects where I’ve zoomed the map. To be honest, a superior option would be if I could manually draw from what geographical location I wanted to pull data.

AirDNA Filters: Performance Metrics

But, again, an equally important consideration, in addition to the physical location or neighborhood, is being able to stratify the percentiles of the Airdna rental data. I’d like to see how well the top 25% of hosts are doing, as well as the bottom 25%.

To get at this question, AirDNA has done something unique. Instead of having the user select the top 90th percentile of hosts, they can choose via how many dollar signs they want.

Upon doing some research on the Airdna website, I understand the following breakdown for each bedroom count:

  • Budget is the lower 20% of listings based on the ADR (average daily rate)
  • Luxury is the top 20% of listings based on the ADR

Here are the following fitlers that AirDNA allows under the Performance metrics:

  • Professionally Managed: both, yes, or no
  • Host Unit Count: All, 1, 2-5, 6-20, 21+
  • Days Available: All, 1-90, 91-180, 181-270, 271-365
  • Rating: <4.0 – 5.0
  • Reviews Count: All, 1-10, 11-19, 20-49, 50-99, 100-199, 200+

Regarding the Days Available metric, you should make note to only select to view those listings available 271-365 days per year. That is listings available for 75%+ of the year. Otherwise the data will be more inaccurate. For example, if you are including a listing only available for 1-90 days, in order to present annual numbers, AirDNA has to extrapolate that data to a year. That’s a lot of assumptions! Remember, we want to limit our assumptions as there are already enough in our rental investment analysis.

If there’s not enough Airdna rental data, then continue selecting down (ie 181-270 days) understanding that it’s dirtying your market data.

Finally, one important note about Reviews Count. One of the ways I am analyzing the best US short term rental markets is by summing the total reviews of listings on the first page of the Airbnb search. Why? Join my Profitable Properties Program. Just kidding! But, not really.

The reason I count the reviews is because if many listings have 200, 300, 400, 500, or even 600+ reviews, why do you think that is? There’s only one reason. Profitability! If a listing has 100 reviews, that’s good. A listing with 200 reviews is likely a few years in the market. If you’re seeing various listings at 300+, take note.

I even identified one market with 3,535 total reviews between the 18 listings on the first page of Airbnb search. That’s a whopping 196 reviews per listing!

I can tell you without much doubt this market is very profitable. Wait..

wait..

Ok. Back. I just reached out to a real estate agent in that market. I got all excited talking about this vacation rental market. And the homes aren’t even that expensive! I’m seeing plenty in the $250-$750k range. That’s with an annurla revenue of $50-$100k.

Anyways, let’s move on to maybe the most important section of this entire AirDNA review and guide.

How Accurate is AirDNA Market Data?

It doesn’t actually matter. I know that might be surprising to hear, but please let me explain.

Maybe you have heard this uttered: profits are in the details.

Or something like that.

Even if you hadn’t, it’s true. Profits are in the details.

They’re not in general market data or a Market Score number summarizing that genrelized market data.

The more verifiable data you have on your chosen market, the better vacation rental investment decision you will be able to make. The more opportunities you will see. Ultimate, the more profitable property you will buy.

Key word: verifiable.

It doesn’t matter how accurate AirDNA market data is because you will verify it anyway. If you can’t verify it, as you cannot with much of the AirDNA data, then it becomes useless data and not to be relied upon more than to give you ideas to further your Airbnb investing analysis.

Why do I feel this way? Becuase all numbers lie. I know this intimately as a Certified Public Accountant. I worked with numbers every day for years of my life.

Give me a set of data and I could make a poor investment seem like a great one. It all depends on what information I want to include. And how I wanted to filter that information to present my case.

For example, maybe I only look at the top 50% of a market, or the top 25% of a market. Or maybe I only include data from last year or the trailing 12 months. Or maybe I only include all listings or only listings with a 4.7 rating or higher or only listings with 25+ reviews or only listings that are older than 3 months. All of these decisions will change the data I present to you and if I have a pre-exiting bias, as all of us do, then I’ll just choose the filters that further what I want to present.

This is true with all numbers whether it’s crime rates, travel statistics, or Airbnb STR data analysis.

You must verify what’s behind a particular number before you can rely on it. What that means is understanding the methodology used in developing the rental market statistics.

Back to our Tulsa market. I see for Luxury listings with 4+ bedrooms, the market revenue is $145,000 from 49 listings. If I stopped there, I would likely make a bad rental investment. Why?

Let’s dig into the numbers a bit. I see one of the listings have a revenue potential of nearly a million dollars. Whoa!

vacation rental market investing analysis wirth airdna market dashboard

But with zero reviews…?

But it’s been available for 366 days? With an average daily rate of $6,400? And an occupancy rate of only 36%. I think even a non-technical host would know something wrong here if they knew to investigate the numbers presented.

When you click open this listing, it has zero reviews and has a daily rate of $6,400 with a minimum of 7 nights and a maximum of 8 nights. Zero reviews over the entire prior year. So AirDNA is relying on this listing’s price of $6,400 to determine their revenue potential presented to Airbnb investors. But this listing clearly has no idea what they’re doing.

How much would the $145,000 revenue potential for this market segment change if this listing were removed?

I hope you see why you must verify as much of the Airdna market data as you can. It’s like measuring twice and cutting once for my architects.

How to use AirDNA?

The best way to use AirDNA is by selecting as many filters as possible. You want to avoid general market data in favor of specific listing data.

In Tulsa, Oklahoma that means I would select these filters:

  • Listing Type: Entire Place
  • Bedrooms: 4
  • Bathrooms: 3-6+
  • Price Tier: Luxury $$$$$
  • Days Available: 271-365
  • Rating: 4.7 – 5.0

Here’s what the dashboard shows with these filters. There are only five listings in this data set.

best short term rental airbnb markets airdna

Next, I would click the STR Listings tab. The first thing to catch my attention is that one of these listings has only three reviews. This would be unlikely for a listing available for 271+ days over the past year. The reason is due to a duplicate listing. Middle top tow and bottom-left (below).

short term rental investing investment airdna

One is on Airbnb and one is on VRBO. This calls into question how accurate the AirDNA rental data is if their system can’t match two identical listings with the same photos, but listed on two of the largest OTAs, VRBO and Airbnb.

After some investigation, it looks even worse because AirDNA has an intelligent matching algorithm leveraging 14 factors to address this specific and common issue.

airdna duplicate airbnblisting problem algorithm

I also noticed that all of the rentals are in different neighborhoods. It’s always good to have an expectation and compare that with what you’re seeing. My expectation was that all these listings (given the tight filters) would be similarly located, but that’s not at all the case.

That seems to be the end of the road with my Pro AirDNA subscription. I need to upgrade to Advanced and pay 50x more to see listing-specific data. Until you buy more Airbnb Boosters or Listing Optimizations, I can’t afford that (: 🙏

how to use airdna cost

Let’s go back to AllTheRooms Analytics and filter the data the same as we had on AirDNA.

I am going to click open each of the listings, starting with the highest revenue.

And..

I found it.

us vacation rental all the rooms airbn bdata tulsa luxury

So, let’s click in and see what Airbnb listing data AllTheRooms provides.

allthe rooms data analytics rental market luxury

We can see this listings is charging something way up at the top of the market. If we can afford it, this should be our aim. One larger vacation rental is better and more proftiable than two smaller rentals.

We already see one potential price optimization. This host does not provide a monthly discount. By providing one, especially in the slow season, could net some extra revenue and a higher occupancy.

HOLD THE PHONE! No freakin’ way folks. I do not believe it.

This listing does NOT use any dynamic pricing tool. Ding ding ding!! I’d buy it tomorrow if it were on sale because I know that with this one change, I could increase revenue by 25% at a minimum! That’s because I’d fill up more low-demand days at lower prices, and I’d fill some of those high-demand days at more than $600.

But I know the host is probably selling it (if they were) based on their actual results which I know to not be optimized. That’s a 25%+ bargain.

vrbo airbnb rental statistics stats all the rooms

I really like this graph (below) showing an overlay of average daily rate and occupancy. Something happened in October of last year, plummeting their occupancy. Maybe new owners?

all the rooms listing specific calendar revenue data luxury str market

AllTheRooms assigns a VRPS score to all listings. This one shows a 0 because of no recent bookings. We can see the historical VRPS is only 632. This is bad. The VRPS for The Belmonte Penthosue is 999. Something is wrong with this listing. Maybe STR regulation issues? Maybe the host just doesn’t know what they’re doing? This could very well be an opportunity needle in a haystack.

what is the vrps metric all the rooms mean

Actually, I just reached out to this listing, haha. The host had their short-term rental property management company name listed on the profile. Searched Google, and bam.

How Much Does AirDNA Cost?

“If you’re looking for something a little more comprehensive..” said every sleezy saleman ever.

I received this email from AirDNA on January 23rd, a few weeks after I subscribed.

As I thought I already had subscribed to the top tier, I replied to the saleman asking for clarification.

You ain’t got shit son! He said in a more professional tone, requesting me to book a video sales call so he could “understand my needs better”.

After a few more back-and-forths, I insisted on knowing the minimum cost without a video sales call and the sales rep obliged. Talk about sticker shock!

So AirDNA wants me to go from paying $25 per month to $9,600+ per year. Wow.

Not only surprised, but pissed off. So they sold me some incomplete data, which I was already aware of, full knowing their intention of getting a percentage of these customers into their highest tier after they’re unsatisfied with what they already bought.

That reads ‘start from 9,600 USD’. I can image that price easily getting to double, tripe, or quadruple that annual cost for something ‘just a little bit more comprehensive.’

I did not subscribe to that plan and I don’t recommend you do so either unless:

  • you know exactly what you’re seeking before going in,
  • confirming they have the data and it’s accurate data,
  • they have a knowledgeable customer service rep available to help you with any and all doubts rather than forwarding an FAQ article
  • and, most importantly, the investment of $10, $20, or $30k+ will be recouped.

AirDNA should be looked at as an investment. At $25 per month, I’m probably recoupoing my investment. At $1,000+, paid annually, I’m not so sure. And only if I was certain would I subscribe to that level.

For the rest of us plebs, having to use peasant data, here are those monthly prices.

how much does airdna cost?

I started, as I always do, with the free version and made two upgrades as I needed more data. The free version is nearly useless, as is the Basic paid version, so I suggest if you’re to use AirDNA market data tool to go straight up to the ‘Most Popular’ Pro plan.

My Take: AirDNA Best Places to Invest Blog

Every year, AirDNA releases a blog titled “Best Places to Invest in Short-Term Rentals”. This year, I critically reviewed the article on my YouTube channel.

AirDNA Revenue Calculator (prior AirDNA Rentalizer)

This service used to be called AirDNA Rentalizer, which they have incorporated into the subscription. It’s available for all service areas both inside and outside of the USA. I talked about the Rentalizer in a prior blog post on AirDNA. You’re probably curious how accurate is the AirDNA revenue calculator?

It’s tough to judge the accuracy of the tool. But, it does appear to be decently accurate. At least within the ballpark, but keep in mind the more luxurious and non-standard your Airbnb is, the less accurate this tool will be.

airdna revenue calculator accurate exmaple

For example, the AirDNA revenue calculator says The Belmonte Penthouse could earn $105,000. That’s twice as much as the last host was making and about 60% of what I’m making. So you see the large variation. I prefer estimating the annual revenue based on the occupancy and daily rates.

Similar with the operating expense estimate. An interesting offering, but you’ll want to get a more accurate number for your specific rental property. You can do that with a spreadsheet I provide to all lifetime purchasers of my Profitable Properties Program.

Did you know that I have an Airbnb revenue calculator? Answer four questions, and I will provide a low and expected annual revenue estimate as discussed above. Interestingly, here is the estimation for The Belmonte Penthouse. In year one, I made $152k and year two it was $163k.

accuarate and easy airbnb revenue calculaor optimize airbnb

AirDNA For Sale Module

The properties listed here are not short-term rentals. I think it would be cool if Airbnb worked in a feature where a guest or viewer of the online listing could send the host a notification that they’re interested in buying the rental. But Airbnb has been stagnant for eight years now, one can wish!

The properties don’t update as you move the map. In the case of Tulsa, I’m seeing 1,400 For Sale Properties regardless of where I move the map.

This makes the sorting feature less valuable.

us vacation rental for sale properties airdna

When you click into a rental property, you’re provided with a revenue, occupancy, expense, and cap rate estimate.

The cap rate is a short term rental investing term, and you calculate it as follows:

[Net Operating Income (ie Revenue – Expense)] / Current Market Value OR Purchase Price

A generally accepted good capitalization rate for an Airbnb is between 4 – 10%.

The Belmonte Penthouse has a cap rate of 19%.

Within the For Sale AirDNA module, they provide the zone status. This is useful information. But you’ll want to verify it.

zone status airbnb str listing airdna for sales properties

AirDNA Alternative Competitors

The main competitor to AirDNA is AllTheRoom Analytics. Readers of this blog are entitled to a never-before-offered 50% discount for an entire year on any plan.

What I like about AllTheRooms is that all plans include all data. Think of the below prices as the AirDNA Advanced level data.

If you already know what state you want to invest in, then choose STATE subscription. Otherwise, the COUNTRY subscription will be ideal. If you’re open to short term rental investing internationally, like me, please choose GLOBAL.

Click to learn more about AllTheRooms vacation rental market analytics tool. Use code OPTIMIZE50 for 50% off any subscription.

all the rooms airbnb analytics airdna competitior promo code free trial 50% off str data tool

I know of Mashvisor, but you must subscribe there for at least three months at $360 minimum. You also have STR Insights to choose from with a monthly cost of $200.

AirDNA Host Tools

Did you know that AirDNA provides four more tools included with your subscription?

Manager Calendar

Basically, a trick getting you to give AirDNA your listing’s calendar data for free to increase their data accuracy. You must connect your calendar to use the AirDNA Smart Rates™ dynamic pricing tool. My preferred dynamic pricing tool has been PriceLabs since 2018.

Comp Sets

airdna comp set tool review tutorila guide

Maybe my favorite part of AirDNA. This neat tool allows you to filter more specifically than Airbnb allows to what you believe is your direct competition and then not only see their stats but compare them to your own in the next tool. You should be scouting your competition on Airbnb regardless of this tool and creating a private wishlist on Airbnb to keep tabs on them. The only problem is I don’t see my main competitor in the same building as me on the list of potential competitors and I’m not sure why.

Pacing Data

AirDNA’s Pacing Data is interesting. It allows you to spy on your competition. You can see that I’m rated a 78 up to 100 based on the five direct rental competitors I’ve selected from the Comp Sets tool. And I gotta say, I’m a little nervous.

airdna pacing data compe sets tool subscriptoin free trial

You can see over the next sixty days that much of my competition is already booked and my July calendar is totally empty. My BLT is 15 days while my competition is closer to 35 days so this is one reason. Nevertheless, I feel a small bead of sweat on my forehead right about now.

Unfortunately, the other three bubbles (above the chart) I have no idea what they mean, and the ⓘ doesn’t show anything when hovered or clicked. Though I will say the design of those metrics remind me of another Airbnb data tool called Intelihost. I’ve recorded an Intelihost video tutorial and a blog review of Intelihost.

Below is a screenshot of the AirDNA Smart Rates™ (purple) compared to my rates (green) compared to my comp set rates (pink). You can see that Smart Rates™ has much less variation between weekdays and weekends and heavily increases prices further out. Both of these preferences are inferior to the PriceLabs algorithm.

This is still a neat chart because it clearly shows that my prices are significantly higher than my competition’s. This is partly why their BLT is much higher (ie they’re much cheaper).

airdna smart rates dynamic intelligent pricing tool software

Conclusion: Is AirDNA worth the cost?

Phew! You made it. That is a looong blog post.

If you skipped down here first without reading my AirDNA tutorial, then I’ll say, yes, the AirDNA market data is worth the cost with one big caveat: You must verify all the Airbnb data.

I think that $25 is the appropriate cost for this rental market data. Much more and the use cases would be limited. I’d likely only subscribe for a month when I had a pre-existing set of questions to be answered.

But at $25 per month, it’s in line with many existing subscription based Airbnb analytics tools.

Now you know all about Airbnb data and how to analyze it with both AirDNA and AllTheRooms. I hope you got tremendous value. Thank you for your support.

About Danny Rusteen

Starting in 2012, Danny has been an Airbnb employee, Superhost, and Airbnb property manager. Danny lives in Airbnbs (2,000 nights). As a guest, Danny has traveled to 36 countries and sifted through thousands of Airbnb listings, so he knows what makes a listing stand out and how to offer a world-class experience to your guest. Follow his journey.

GET DANNY’S BOOKS

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