Every few weeks someone sends me a screenshot before they buy a house. It is almost always the same picture: an AirDNA Rentalizer estimate for a three or four bedroom home, a big annual revenue figure at the top, an occupancy percentage underneath, and a question typed above it. "Is this real?" In 2026 I get that question more than any pricing question, because AirDNA's own July 2026 Midyear Outlook called this a better year for short-term rental investors than most people expected, and buyers are back.
My honest answer is that AirDNA is accurate at the thing it was built to measure, which is market-level performance, and much less accurate at the thing most buyers use it for, which is predicting what one specific property will pay them in its first year. The gap between those two uses is where I see investors lose money. In this article I will show you exactly where an estimate comes from, the five errors I find when I audit investor projections, and a worked example that turns an $80,000 headline into the number you should actually underwrite.
Is AirDNA Accurate for a Single Property?
AirDNA is accurate enough for a single property to show whether a deal is in the right range, and not accurate enough to underwrite a mortgage on. A Rentalizer figure for one address is a weighted average of nearby comparable listings, so it inherits their differences from your home. In 2026, treat it as a starting range.
AirDNA is a short-term rental data company that estimates listing performance from public calendar and price data, supplemented by booking data shared by partner property managers. That definition matters, because it tells you what kind of error to expect. The company says it tracks more than 10 million vacation rentals across 120,000 markets, and at that scale the errors on individual listings tend to cancel out. AirDNA's accuracy page reports market-level revenue accuracy in the mid to high 90s percent when compared with actual reported figures. I have no reason to dispute that for markets.
The problem is that nobody buys a market. You buy one house, on one street, with one set of photos and one hot tub that may or may not work. When you shrink the sample from a whole market down to the handful of comps near one address, the averaging stops protecting you.
Market accuracy versus property accuracy
Awning's 2026 review of AirDNA estimates that individual property projections run 15 to 30 percent off actual performance, and sometimes further for homes that do not match the typical profile of the area. That is not a flaw unique to one company. Any model that predicts one listing from its neighbours will miss by that much, because two three-bedroom homes a mile apart can earn very different amounts depending on reviews, photos, layout, parking and pricing discipline.
When I audit a buyer's projection, the first question I ask is simple: which part of this number is the market, and which part is an assumption about this house? The market part is usually defensible. The house part is usually where the optimism lives.
Bottom line: AirDNA is accurate for markets and approximate for properties, so a single Rentalizer estimate should narrow your search, not justify your offer price.
The 2026 Market Behind the Estimates
The 2026 short-term rental market is steadier than the headlines of 2023 suggested, and that stability makes AirDNA's market-level estimates more useful this year. AirDNA's July 2026 Midyear Outlook forecasts US occupancy averaging 57.4 percent in 2026, slightly above the pre-pandemic average of 57.0 percent, with RevPAR up 2.9 percent on stronger nightly rates.
The same July 2026 report projects demand and available listings each growing 2.7 percent. Compare that with AirDNA's December 2025 outlook, which expected listings to grow 4.6 percent and described that pace as well below the 20 percent peak expansion of 2021 and 2022. Supply growth slowed more than the forecasters expected, and slower supply is the main reason hosts have had room to push rates. AirDNA's midyear data shows nightly rate growth accelerating from 0.7 percent year over year in January 2026 to about 3 percent by spring.
Why forecast revisions matter to a buyer
Here is the part most AirDNA reviews skip. The market forecast itself moved during the year. AirDNA's December 2025 outlook expected occupancy to ease by about 1 percent and ADR to rise about 1.5 percent in 2026. By July the picture was better. For Philadelphia, the December 2025 report forecast 6.3 percent RevPAR growth for 2026 on World Cup demand, while the July 2026 midyear report showed Philadelphia RevPAR up 10.1 percent year to date.
That is not a criticism. Forecasting is hard and good forecasters revise. The lesson for a buyer is that a Rentalizer figure you pull in September 2026 is built on trailing data and a forward view that will change again. If a deal only works at the exact number on the screen, the deal does not work.
The international picture carries its own warning. AirDNA's midyear 2026 report notes international short-term rental demand into the US running 12 percent below the previous spring, with Canadian demand down 32 percent from 2024 levels. In a market that relied on cross-border guests, trailing comps from 2024 will overstate what a new listing earns now. I covered the wider profitability question in my piece on whether Airbnb is still profitable.
Bottom line: The 2026 market backdrop is supportive, but AirDNA's own forecasts changed between December 2025 and July 2026, so build your underwriting to survive a revision in either direction.
AirDNA Estimates Come From Comparable Homes
AirDNA's Rentalizer estimates come from a weighted average of comparable listings near the address you enter. AirDNA's help center says the tool searches within roughly a 10-mile (15 km) radius and weights comps by distance and by similarity in bedrooms, bathrooms and guest count, then adjusts for seasonality, demand and revenue growth in the market.
Read that description slowly, because it explains most of the errors I find. A 10-mile radius is a lot of ground. In a city it can cross five neighbourhoods with completely different guest profiles. In a mountain or lake market it can mix waterfront homes with homes that sit behind a gas station. Bedroom and guest count are good matching variables, but they say nothing about the view, the pool, the parking, the review score or how well the comp is priced.
What the comp set cannot see
- Review score and review count, which drive conversion and search placement on Airbnb.
- Photo quality and listing copy, which decide whether a guest clicks at all.
- Amenities that change the price ceiling: hot tubs, pools, game rooms, ski access, beach access.
- Whether the comp is professionally priced or left on a flat rate all year.
- Whether the comp's blocked nights were owner stays, maintenance, or genuine bookings on another channel.
AirDNA's help documentation mentions a comp set strength indicator, and lower consistency among the comparables produces lower confidence. I tell every buyer to look at that signal before the revenue figure. A weak comp set with a big revenue number is a warning, not an opportunity.
Why the top performers pull the average up
In the portfolio audits our team runs, comp sets in thin markets often contain one or two exceptional listings: a home with 400 reviews, a Guest Favorite badge and a pricing strategy tuned for years. Those listings earn far more than a new home will in its first year, and a weighted average gives them real influence. The Haus analysis of predictive revenue tools makes the same point about rural markets with only a few dozen active listings, where a single outlier can move the projection.
Bottom line: AirDNA estimates are only as good as the comparable homes behind them, so open the comp list, remove the ones that are not truly comparable, and see how far the number moves.
AirDNA Revenue Is Gross, Not Your Payout
AirDNA revenue is a gross booking figure, not the money an owner receives. AirDNA's Rentalizer documentation says projected revenue includes the cleaning fee and excludes the host fee, other fees and taxes. In 2026 that host fee is Airbnb's 15.5 percent host-only fee, which applies to the full booking subtotal, cleaning fee included.
This is the single most common error I see in investor spreadsheets. The buyer takes the Rentalizer revenue, subtracts a mortgage, insurance, utilities and maybe a management fee, and calls the rest profit. They forget that the headline already contains cleaning fees that belong to the cleaner, and that Airbnb takes its commission before a cent reaches the bank.
The 2026 fee change makes this worse
Airbnb's Resource Center explains that it combined the host and guest fees into a single 15.5 percent host service fee, with a deadline to adjust prices of September 15, 2026 for hosts outside the European Economic Area and October 13, 2026 for hosts inside it or in Switzerland. Airbnb states that listings in Brazil and Mexico stay on a 16 percent single fee.
Under the old split-fee model, most of Airbnb's commission sat on the guest's side of the checkout. A projection built from comps that were still on split fees during the trailing twelve months mixes two fee worlds. The gross revenue a guest paid may look similar, but the host's share has changed. When I rebuild a buyer's model, I apply 15.5 percent to every Airbnb booking in the forecast, including cleaning, and the number usually drops by more than they expected.
| Line in the estimate | Included in the Rentalizer revenue? | What I do in the audit |
|---|---|---|
| Nightly rate revenue | Yes | Keep, then adjust for ramp-up and owner blocks |
| Cleaning fees charged to guests | Yes | Keep as revenue, then subtract what the cleaner is paid |
| Airbnb 15.5 percent host-only fee | No, not deducted | Subtract from the full booking subtotal |
| Occupancy and lodging taxes | No | Exclude from revenue entirely; they pass through to the authority |
| Owner stays and maintenance blocks | Not modelled for your home | Remove those nights from sellable inventory |
Bottom line: Before you compare an AirDNA figure with a mortgage payment, take out cleaning costs and Airbnb's 15.5 percent fee, or you are comparing gross revenue with a net expense.
Five Errors I Find in Investor Projections
AirDNA projections go wrong in investor spreadsheets for five repeatable reasons: a polluted comp set, gross revenue treated as net, no ramp-up for a new listing, owner blocks ignored, and trailing data from a market that has since changed. In the projection audits I run in 2026, at least two of these five show up almost every time.
1. The comp set includes homes that are not comparable
A four-bedroom house with a pool is not comparable to a four-bedroom house without one, even if the tool matched them on bedrooms and guests. When I audit a projection, I open every comp and throw out the ones with a feature the target home lacks, or the other way round. Often three of the top five earners leave the set, and the estimate falls.
2. Gross revenue treated as owner income
As covered above, the Rentalizer figure includes cleaning fees and excludes the platform fee. Treating it as income overstates cash flow by the cleaning cost plus Airbnb's 15.5 percent host-only fee on every booking.
3. No ramp-up for a new listing
A new listing has zero reviews. Comps have hundreds. Awning's 2026 review suggests new hosts plan on 60 to 75 percent of the Rentalizer estimate for year one. I would not apply a single blanket haircut, but I agree with the direction. The first 90 days are about earning reviews, and that means pricing below the stabilised rate on purpose.
4. Owner blocks and maintenance ignored
AirDNA's help center states that Rentalizer projections assume full availability for 365 days. Almost no owner achieves that. Deep cleans, repairs, a family week at the lake and a slow week you decide not to sell all come out of sellable inventory. I wrote about the real price of those nights in my article on what owner stays actually cost.
5. Trailing data from a market that has moved
Rentalizer looks backward at comp performance and then adjusts. In markets where AirDNA's 2026 midyear report shows international demand 12 percent below last spring, or where a city has tightened permits since the trailing period, the comps earned money under conditions a new buyer will not get. Regulation is the sharpest version of this. A comp set can look perfect and still describe listings that would not get a permit today.
Bottom line: Most bad AirDNA-based projections are not caused by bad data; they are caused by five fixable modelling shortcuts, and fixing them before an offer is far cheaper than discovering them after closing.
What Does an Honest Projection Look Like?
An honest short-term rental projection starts from the AirDNA estimate and then removes what the estimate cannot know about your home: owner blocks, the first-year ramp, Airbnb's 15.5 percent host fee and the cost of cleaning. The worked example below, with illustrative numbers, shows how an $80,000 headline for 2026 becomes about $45,800 of year-one cash.
Example: an $80,000 Rentalizer-style estimate
Take a hypothetical three-bedroom house where the estimate shows $80,000 of annual revenue at 65 percent occupancy. These are example numbers, not a real property.
- Nights sold in the estimate: 365 nights x 65 percent = about 237 nights.
- Cleaning fees inside the estimate: at an average stay of 3.2 nights, 237 / 3.2 = about 74 stays. At a $160 guest cleaning fee, that is $11,840.
- Implied nightly revenue: $80,000 minus $11,840 = $68,160, so the implied ADR is $68,160 / 237 = about $288.
Now I rebuild year one for a brand-new listing.
- Owner and maintenance blocks: 20 nights, so sellable nights fall from 365 to 345.
- Year-one ramp: I assume 58 percent occupancy on sellable nights instead of 65 percent, and an ADR about 5 percent below the comps while reviews build, so $273. That gives 345 x 58 percent = 200 nights, and 200 x $273 = $54,600 of nightly revenue.
- Cleaning fees: 200 / 3.2 = about 63 stays, and 63 x $160 = $10,080. Gross booking revenue is $54,600 + $10,080 = $64,680.
- Airbnb host-only fee: 15.5 percent x $64,680 = $10,025. Payout is $54,655.
- Cleaner cost: 63 turns x $140 = $8,820. Cash to the owner before mortgage, utilities, insurance, supplies and taxes: $45,835.
Year two, once the listing has reviews, looks closer to the comps: 345 x 63 percent = about 217 nights at $288, which is $62,496 of nightly revenue. With 68 stays, cleaning fees add $10,880, so gross is $73,376. The 15.5 percent fee is $11,373, payout is $62,003, cleaning costs are $9,520, and cash to the owner is $52,483.
| Example line | Headline estimate | Year 1 rebuilt | Year 2 rebuilt |
|---|---|---|---|
| Sellable nights | 365 | 345 | 345 |
| Occupancy | 65% | 58% | 63% |
| Nights sold | 237 | 200 | 217 |
| ADR | $288 | $273 | $288 |
| Gross revenue incl. cleaning | $80,000 | $64,680 | $73,376 |
| Airbnb fee at 15.5% | Not deducted | $10,025 | $11,373 |
| Cleaner cost | Not deducted | $8,820 | $9,520 |
| Cash to owner before other costs | Not shown | $45,835 | $52,483 |
Notice what happened. Gross revenue in year one landed at about 81 percent of the headline, which is inside the range most reviewers describe. But cash to the owner landed at about 57 percent of the headline. The buyer who underwrote the $80,000 was not wrong about the market. They were wrong about which number to divide the mortgage into.
Bottom line: In this example, the honest year-one figure is about 57 percent of the AirDNA headline, and that is the number your financing should survive.
AirDNA Numbers and the First-Year Ramp
AirDNA numbers describe established listings, and a new Airbnb listing does not behave like an established one in its first year. A new listing has no reviews, no ranking history and no repeat guests, so in 2026 I plan for lower occupancy and a lower rate for the first three to six months, then a climb toward the comp set.
AirDNA's July 2026 Midyear Outlook projects demand and supply both growing 2.7 percent, so a new listing is not riding a wave of unmet demand; it is competing for guests that established listings already reach. The ramp is not only about reviews. Airbnb search placement rewards listings that convert, and a new listing has no conversion history. That is why I launch new homes priced to fill specific gaps in the comp calendar, not priced at the comp average. The goal of the first 90 days is a stack of five-star reviews and a booking pattern the algorithm can read. Revenue comes second, and it comes faster because of the first.
How I set the ramp in a forecast
- Months one to three: occupancy 10 to 15 points below the cleaned comp set, ADR 8 to 12 percent below.
- Months four to six: occupancy 5 points below, ADR within 5 percent of the comps.
- From month seven: stabilised, assuming reviews average 4.8 or better.
- If the launch falls in low season, extend the ramp, because you have fewer bookings to earn reviews from.
These are the planning ranges I use as starting assumptions, not rules and not results from any one property. They change by market. A dense urban market with fast-moving demand ramps quicker than a lake town with six good weeks a year. The pricing side of this, how to position a new listing against the comp set without giving the calendar away, is the work behind my Airbnb pricing strategy service.
Bottom line: A 2026 AirDNA estimate is a stabilised number, so model at least six months of ramp before you expect a new listing to earn it.
How Should You Use AirDNA Before Buying?
Use AirDNA before buying to choose a market, check seasonality and find comparable listings, then build your own property-level forecast from those comps. AirDNA does the research that would take a buyer weeks, and it does it well. The mistake is letting its single revenue figure replace your own underwriting in 2026.
The pre-offer checklist I give buyers
- Pull the estimate, then open the comp list and remove every listing that does not truly match on location, amenities and guest capacity.
- Keep ten clean comps. Check each one's review count, review score and calendar by hand for the next 90 days.
- Rebuild revenue from nights and ADR, split out cleaning fees, and apply Airbnb's 15.5 percent host-only fee to the whole subtotal.
- Remove owner stays and maintenance nights from sellable inventory.
- Apply a first-year ramp, then check that the deal still covers debt service in year one, not only in year two.
- Run a downside case at 15 to 20 percent below your base case, which is the lower end of the error band reviewers describe for property estimates.
- Confirm the permit and regulation position for the exact address with the city, not with the listing agent.
- Compare against the seller's actual booking statements if the home is already a rental, and ask for payout reports, not screenshots of gross revenue.
Where AirDNA is strongest
Market selection is where AirDNA earns its fee. Comparing seasonality curves across three candidate markets, watching supply growth and spotting where rate growth is accelerating, as AirDNA's 2026 midyear report showed for markets like San Francisco at 12.1 percent RevPAR growth and Anaheim at 11.0 percent, is exactly the kind of market-level view the data does well. Once you own the home, the question changes from "what could this earn" to "is it earning what it should", which I cover in telling if your Airbnb is underpriced.
Bottom line: Let AirDNA pick the market and the comps, then let your own cleaned-up forecast decide the price you offer.
Frequently Asked Questions
Is AirDNA accurate for Airbnb revenue?
AirDNA is accurate for market-level Airbnb revenue trends and approximate for a single property. Awning's 2026 review puts individual property estimates 15 to 30 percent off actual performance in either direction. Use it to judge a market and find comps, then build your own forecast for the specific home before you rely on the number.
Does AirDNA include cleaning fees in revenue?
Yes. AirDNA's Rentalizer help documentation says projected revenue includes the cleaning fee and excludes the host fee, other fees and taxes. That means the headline is gross booking revenue. To estimate what the owner receives, subtract what you pay cleaners and Airbnb's 15.5 percent host-only fee, which applies to the full booking subtotal.
Why is the AirDNA estimate higher than what the seller actually earned?
The AirDNA estimate is usually higher than a seller's actual results because it averages comparable homes that may be better reviewed, better priced or better equipped, and because it assumes 365 available nights. A seller's real statements include owner blocks, weaker months and management gaps. Always ask for payout reports and compare both numbers on the same gross or net basis.
How much should I discount an AirDNA estimate for year one?
For a brand-new listing, I plan year-one gross revenue at roughly 75 to 85 percent of a cleaned-up AirDNA estimate, and cash to the owner lower still after fees and cleaning. Awning's 2026 review suggests planning on 60 to 75 percent of the raw Rentalizer figure. Rebuild from nights and ADR rather than applying one blanket haircut.
Is AirDNA accurate in small or rural markets?
AirDNA is less accurate in small or rural markets because the comp set is thin and one exceptional listing can pull the weighted average up. Homes in these markets also differ more from each other, in views, access and amenities. In a market with only a few dozen active listings, check every comp by hand and weight your own judgement more heavily.
Do I need a revenue management consultant before buying an Airbnb?
You do not need a revenue management consultant for one home in a dense market if you can rebuild the forecast yourself with the checklist in this article. Bring one in for a portfolio purchase, a thin or seasonal market, or a deal that only works at the top of the range. Alaa Elhadi and the Revenuenaire team build independent forecasts through our Airbnb revenue management consulting work.
Can I use AirDNA data to set my nightly prices?
AirDNA market data can inform nightly prices by showing comp rates, seasonality and future occupancy, but it should not set them on its own. Pricing needs daily decisions about your own calendar, lead time, minimum stays and events. Use the market data as an input and review your own booking pace against the comp set every week.
My Verdict on AirDNA
AirDNA is a good research tool that gets blamed for decisions people make with it. At market level it is accurate, and its 2026 data on supply, rates and seasonality is worth paying attention to. At property level it gives you a stabilised gross figure that assumes a full calendar and an experienced listing. Your first year will not look like that, and your bank account will not see gross revenue. Clean the comps, split out cleaning, apply the 15.5 percent host fee, block your own nights and model the ramp. If the deal still works, buy it with confidence.
If you would like a second pair of eyes on a projection before you sign, talk to Alaa's team about your numbers.
