How to Analyze Airbnb Comps: 7-Step Short-Term Rental Analysis (2026)

Airbnb comps are the booked performance records of similar short-term rentals near a property you are evaluating, and analyzing them correctly is the single most reliable way to estimate what that property will earn before you buy it. A good comp analysis takes five to ten similar listings, pulls their actual booked nightly rates, occupancy, and seasonality, adjusts for quality and management, and produces a revenue range rather than a single number. Done well, it separates markets where a property will cash-flow from markets where the headline averages hide a problem.

This guide covers what Airbnb comps are, the seven-step comp analysis Awning uses when underwriting properties, where to get the data, a worked example, the mistakes that inflate projections, and what the data says about professionally managed listings. Awning manages 20,000+ properties across all 50 states, so the benchmarks below come from operating at scale.

What Are Airbnb Comps?

Airbnb comps (short for comparables) are existing short-term rental listings that closely match a target property in location, size, type, and amenities, whose historical booking data you use to predict the target's revenue. They serve the same purpose as sales comps in a traditional appraisal, except the output is projected annual revenue instead of market value.

Two rules make comps useful. They are only as good as the match: a four-bedroom lakefront home with a hot tub is not a comp for a two-bedroom condo three miles inland, even if both are "in the same market." And the metrics that matter are booked, not listed: a nightly rate shown on Airbnb is an asking price; a booked rate is what a guest paid.

The core comp metrics you will work with:

• Average daily rate (ADR): total booked revenue divided by booked nights. This is the price guests actually paid, net of discounts.
• Occupancy rate: booked nights divided by available nights. Note that "available" excludes owner blocks, so a listing blocked half the year can show high occupancy on low revenue. Awning's guide to Airbnb occupancy rates covers how to read this correctly.
• RevPAR (revenue per available rental): ADR multiplied by occupancy. This is the metric to compare across comps because it combines pricing power and demand into one number. Some tools call the annual version RevPAN (revenue per available night).
• Seasonality: the month-by-month distribution of revenue.
• Booking lead time: how far in advance guests book. Short lead times mean thin visibility and more exposure to last-minute price cuts.

How to Analyze Airbnb Comps in 7 Steps

The full process takes two to four hours per property with a paid data tool. Skipping the adjustment and stress-test steps is where most first-time investors go wrong.

1. Define the comp set. Filter to listings that match the target on bedroom count (exact), bathroom count (within one), property type (entire home vs. condo vs. cabin), guest capacity (within two), and headline amenities (pool, hot tub, waterfront, view). Start with a radius of one to three miles in dense markets and up to ten miles in rural or resort markets, and tighten the radius until you have five to twelve listings with at least 12 months of history. Exclude listings with fewer than 90 booked nights in the trailing year; they are new, blocked, or failing.
2. Pull the performance metrics. For each comp, record trailing-12-month ADR, occupancy, RevPAR, annual revenue, review count, average rating, and the monthly revenue curve. Note each comp's booking lead time and minimum-stay rules if the tool exposes them.
3. Map seasonality and lead time. Stack the monthly revenue curves for all comps and calculate what share of annual revenue falls in the top three months. If that share is above 45%, the market is highly seasonal and your cash-flow model needs a reserve to cover the off-season mortgage. Check whether peak months book 60 to 120 days out (stable demand) or under 21 days out (price-sensitive demand).
4. Adjust for quality, reviews, and management. Sort your comps into tiers. Listings with 4.9+ ratings, 100+ reviews, professional photography, and a professional manager are the ceiling; new or poorly reviewed listings are the floor. Your target will land somewhere in between depending on how you furnish it and who manages it. Awning's internal benchmark is that a newly launched listing typically takes six to twelve months to reach the review count that unlocks top-tier placement, so year-one projections should sit below the comp median even for a well-executed property.
5. Build the revenue estimate as a range. Set the low case at the 25th percentile of comp RevPAR, the base case at the median, and the high case at the 75th percentile. Multiply each by 365 to get annual revenue. Never use the average; one outlier comp will pull it up by thousands of dollars.
6. Stress-test the range. Reduce the base-case occupancy by five percentage points and ADR by 5% to simulate the supply growth AirDNA projects for 2026, then check whether the property still covers debt service, management, and operating expenses. If the deal only works at the high case, it does not work.
7. Check regulation and supply pipeline. Confirm the property's zoning allows whole-home short-term rentals, whether a permit or cap exists, and whether any ordinance is pending. Then look at how many new listings entered the comp set in the last 12 months. A comp set that grew 15% while RevPAR fell 8% is a warning sign no revenue estimate can fix.

Where Do You Get Airbnb Comp Data?

You have four practical options: paid analytics platforms (AirDNA, Rabbu, Mashvisor), revenue-management tools with market data (PriceLabs), free calculators such as Awning's, and manual research on Airbnb and Vrbo. Most investors use a free estimator to screen markets and a paid platform to underwrite the specific property they plan to buy.

AirDNA is the most widely used source. As of September 2026, according to AirDNA's pricing page, the Free plan includes a limited Rentalizer, the Market Research plan is $125 per month or $34 per month billed annually ($400 per year) and adds customizable Rentalizer, historical market insights, comparable sets, and future demand data, and the Property Manager plan is custom-priced. Its weakness is that estimates for listings it cannot observe (new builds, direct-booking homes) are modeled. Awning's AirDNA review covers accuracy in more detail.

Rabbu offers a free address-level revenue lookup that returns estimated revenue, ADR, and occupancy from nearby comps, with paid reports and subscriptions for full projections. According to Awning's September 2026 Rabbu review, single reports run roughly $25 to $50 and subscriptions $50 to $100 per month, though pricing has shifted with promotions. The main limitation is that Rabbu's comp selection is a black box: you cannot always see why a listing was included.

Mashvisor is oriented toward property search rather than pure STR analytics. As of September 2026, Mashvisor's site lists Lite at $49.99, Standard at $74.99, and Professional at $99.99 per month (billed annually), with neighborhood heatmaps, side-by-side property comparisons, and STR regulation lookups for 500+ cities.

PriceLabs Market Dashboards let you build custom comp sets filtered by review count, occupancy, and amenities, and show future occupancy on the books, new bookings and cancellations in the last 7, 14, and 30 days, and booked (not listed) prices by stay date. PriceLabs' dynamic pricing product is listed at $14.49 per listing per month as of September 2026; Market Dashboards are sold separately and pricing is not published on the main pricing page, so request a quote.

Awning's free Airbnb calculator. The Awning Airbnb calculator estimates annual revenue, ADR, occupancy, seasonal revenue patterns, and comparable nearby listings for any U.S. address at no cost and with no signup. It is built on booked data from the 20,000+ professionally managed properties in Awning's portfolio rather than scraped listing prices, and updates monthly. Use it as the first pass on any address, then confirm against a second source. For market-level screening, Awning's Airbnb market data pages show occupancy, ADR, and revenue by city.

Manual research on Airbnb and Vrbo. Free, but slow. Search the target area with the right bedroom count, open each listing's calendar, and record booked dates weekly for at least eight weeks. This method never gives you booked ADR, only listed rates, so discount whatever you see by 15% to 25% before using it in a model.

Airbnb Comps Worked Example: Underwriting a 3-Bedroom Cabin

Here is an illustrative example of the seven steps applied to a hypothetical 3-bedroom, 2-bathroom cabin with a hot tub in a mountain market, priced at $525,000. All figures below are illustrative and rounded, not drawn from a specific listing.

Step 1, comp set: 3-bedroom entire-home cabins within five miles, sleeping 6 to 8, with a hot tub, at least 12 months of history, and at least 90 booked nights. That filter returned eight listings.

Steps 2 and 3, metrics and seasonality: the median RevPAR is $142 (between D and E). Stacking the monthly curves shows 41% of annual revenue lands in June through August, with a second bump in October, so this is seasonal but not extreme. Peak-season bookings come in 45 to 90 days out; winter bookings are under three weeks out.

Step 4, adjustments: the two professionally managed comps (A and B) sit 25% to 40% above the median. Comp H is a new listing with 19 reviews, which explains its position at the floor. The target will be furnished new and launched with zero reviews, so year one should be modeled near the 25th percentile, with year two moving toward the median if reviews accumulate on schedule.

Step 5, revenue range:

• Low case (25th percentile, RevPAR about $121): roughly $44,000 per year.
• Base case (median, RevPAR $142): roughly $52,000 per year.
• High case (75th percentile, RevPAR about $172): roughly $63,000 per year.

Step 6, stress test: cutting base-case occupancy by five points (to about 53%) and ADR by 5% takes the base case down to roughly $45,000. With a 25% down payment on $525,000 at the 6.71% 30-year rate Freddie Mac reported on September 3, 2026, annual debt service is about $30,500. Add roughly $9,000 for taxes, insurance, utilities, and maintenance, plus management, and the stressed base case is close to breakeven. At the unstressed base case it produces modest positive cash flow. That is a "negotiate price" result, not a clear yes.

Step 7, regulation and supply: the county requires a short-term rental permit with no cap, and the comp set grew by one listing in the last 12 months. No red flags.

For a deeper look at the return side of this math, see Awning's guide to Airbnb cap rates.

What Are the Most Common Mistakes in Short-Term Rental Analysis?

The most common short-term rental analysis mistakes are using listed rates instead of booked rates, ignoring new supply, and skipping the regulation check. Each one inflates projected revenue in a way that only shows up after closing.

• Using listed rates instead of booked rates. A listing's calendar price is the host's ask. Actual booked ADR runs meaningfully lower once weekly and monthly discounts, last-minute markdowns, and promotional pricing are applied. Awning's calculator page notes that scraped listing prices can overstate revenue by 20% to 40% for this reason. Always use a source that reports booked revenue.
• Ignoring supply growth. AirDNA's 2026 outlook, released December 16, 2025, projected available U.S. listings to grow 4.6% in 2026 with occupancy easing about 1% and ADR up 1.5%. Its July 8, 2026 midyear update revised supply growth to 2.7% with RevPAR up 2.9%, but the direction is the same: more listings competing for demand that is growing only modestly. Every comp analysis should assume the comp set will be larger next year than it is today. Awning's guide to Airbnb market saturation covers how to read these signals at the neighborhood level.
• Skipping regulation. A comp set full of $70,000-a-year listings is irrelevant if the city stopped issuing whole-home permits last spring. Check the ordinance, the permit cap, and any pending council agenda items before you rely on any number.
• Forgetting platform fees. Airbnb is moving all hosts to a single 15.5% host-only service fee by the end of 2026 (Skift, August 2026). Revenue figures in most data tools are gross of that fee, so net it out before it reaches your cash-flow line.

How Much More Do Professionally Managed Listings Earn?

Professionally managed listings out-earn self-managed listings in most U.S. markets, and the gap is driven by nightly rate rather than occupancy. Per an AirROI analysis of trailing-twelve-month data through March 2026, professional operators earned 26% to 113% more annual revenue than individual hosts across six major markets: $52,506 versus $24,711 in Phoenix (113% gap), $45,218 versus $24,003 in Austin (88%), $57,184 versus $37,821 in Scottsdale (51%), $41,652 versus $28,103 in Miami (48%), $57,930 versus $39,673 in Nashville (46%), and $25,663 versus $20,356 in Dallas (26%).

Two findings from that study matter for comp analysis. First, the premium came from ADR: professionals charged 29% to 91% more per night, while individual hosts matched or beat professional occupancy in several markets (Nashville 49% vs. 46%, Dallas 47% vs. 43%). Second, the gap is not universal. A separate AirROI comparison published April 14, 2026 across nine markets found managed listings ahead by 94% in Austin and 87% in Joshua Tree but only 6% in Gatlinburg, and behind by 19% in Destin. In mature beach markets with deep owner expertise, self-management can compete.

The practical implication for your comp set: tag each comp as professionally managed or self-managed and look at the two tiers separately. If the professional tier earns 40% more, that premium has to cover the management fee to be worth it. At Awning's rates (Essential 10% of revenue, Essential Plus 15%, Full Service 18%), a listing earning $52,000 under Full Service would pay $9,360 in management and still net more than a self-managed listing earning $40,000 at the same address. Awning's guide to Airbnb management fees in 2026 compares fee structures across the industry. That premium is what dynamic pricing across 50+ channels is built to capture.

If you would rather see the managed-tier numbers for your own address before you buy, Awning's team runs comp-based revenue projections as part of every onboarding conversation. You can start at Awning's Airbnb management page.

Frequently Asked Questions

What is a comp in Airbnb investing?

A comp is a comparable listing: an existing short-term rental with the same bedroom count, property type, and headline amenities as a property you are evaluating, located close enough to draw the same guests. Its trailing-12-month booked ADR, occupancy, and revenue are used to project what your property would earn.

How many comps do you need to analyze an Airbnb property?

Five to twelve is the practical range. Fewer than five leaves you exposed to one or two outliers; more than twelve usually means the filters are too loose and you are including listings that are not truly comparable. Tighten the radius or the amenity filter until you land in that range.

Is AirDNA accurate for Airbnb comps?

AirDNA is accurate for listings it can observe with a full booking history and less accurate for new listings, direct-booking homes, and rural markets with few data points. Treat its Rentalizer estimate as one input, cross-check it with a second source such as Awning's free calculator or PriceLabs, and always look at the underlying comp set rather than the headline number.

What is a good RevPAR for a short-term rental?

There is no universal figure because RevPAR scales with property size and market. The right test is relative: compare the target's projected RevPAR to the median of its comp set and to the purchase price. A property whose base-case annual revenue exceeds 10% of its price is generally in the range where financing at 2026 rates can work.

How do you analyze an Airbnb property without paying for data?

Use a free estimator such as Awning's Airbnb calculator or Rabbu's free lookup for the revenue range, then verify on Airbnb by tracking the calendars of five to eight similar listings weekly for two months and reading review dates to gauge booking velocity. Discount listed nightly rates by 15% to 25% to approximate booked ADR. This works for screening but is not a substitute for booked data when you are ready to make an offer.

Why does Airbnb market analysis need to include supply growth?

Because revenue per listing is a function of demand divided by listings. AirDNA's December 2025 outlook projected U.S. listing supply to grow 4.6% in 2026, and its July 2026 midyear update put the figure at 2.7%. Either way, a comp set that looks strong today will have more competitors next year, so model a modest occupancy and rate decline rather than assuming the trailing 12 months repeat.

Do professionally managed Airbnbs make more money?

In most markets, yes. AirROI's trailing-twelve-month analysis through March 2026 found professionally operated listings earned 26% to 113% more than individually hosted ones across six major U.S. markets, driven mainly by 29% to 91% higher nightly rates. The gap is smaller or reversed in a few mature beach markets such as Gatlinburg and Destin, so check the split inside your own comp set.

Related Resources

• How to Analyze Airbnb Investment Properties: Listings, Comps, and Revenue Tips
• How to Choose the Right City for Your Airbnb Investment
• AirDNA vs. Rabbu: Which Data Tool Is Better for Investors?
• Mashvisor Review: Pricing, Accuracy, and Alternatives
• Airbnb Profit Margin Benchmarks 2026 by Market Type
• Top Airbnb Markets in the U.S.