Airbnb Occupancy Rate: How to Calculate with ADR and RevPAR

The occupancy rate on Airbnb is the number of sold nights divided by the number of available nights in the period, multiplied by one hundred. The math fits on one line, but it hides two pieces of information that decide if the month was good: which nights you called available and how much each sold night yielded.

The worked examples below use arbitrary monetary units (u.), not foreign-market prices. A rule of thumb circulates among hosts that seems obvious: it is better to have 80% of the month booked at 120 u. than 100% at 100 u. Do the math for a 30-night month. That is 24 nights at 120 u., or 2,880 u., against 30 nights at 100 u., or 3,000 u. The rule loses. It only becomes valid when the cost of each occupied night is factored in, and that is exactly the part a full calendar does not show.

This guide shows how to calculate occupancy without getting the denominator wrong, what average daily rate (ADR) and RevPAR are, the rule that dictates how much the nightly rate needs to rise when occupancy drops, and a ready-to-copy spreadsheet. What to do with the number when adjusting prices is covered in the guide on how to price your nightly rate in four layers.

Main takeaways

• Occupancy is sold nights over available nights; the same month yields 60%, 72%, or 78% depending on the denominator.
• Average daily rate (ADR) is the nightly revenue divided by sold nights, excluding the cleaning fee.
• RevPAR combines both: occupancy multiplied by average daily rate.
• Occupancy dropping from 90% to 70% requires a nightly rate almost 29% higher to preserve gross RevPAR, before changes in costs.

How to calculate the Airbnb occupancy rate?

Divide the sold nights by the available nights in the period and multiply by one hundred. In a month where you had 25 nights for sale and sold 18, the occupancy is 72%.

In the definition we use throughout the blog, the occupancy rate is the fraction of sold nights over the available nights in the period. The Airbnb Help Center on occupancy and pricing data uses the same calculation: booked nights divided by the total nights available for booking. The dashboard is located in Insights, under the Occupancy and rates area, and shows blocked nights, booked nights, and the average price per night alongside it. It also compares your listing with similar listings in the area. This data appears for those who have activated professional hosting tools in their account settings, and the full version opens in a desktop browser. If the performance tab does not appear, the first step is to activate these tools, as the help center advises. Screen labels change with app updates, but the underlying division remains the same.

Sometimes hosts confuse local occupancy taxes or service fee taxes on receipts with this performance metric. The occupancy rate in this guide is a performance statistic that does not appear on the receipt and costs nothing.

Which nights go into the occupancy denominator?

The nights you actually put up for sale go in, and the ones you took off the market by your own decision come out. This is where the same month turns into three different numbers, and it is rarely disclosed which denominator was used.

Think of a 30-night month, as an example, where you sold 18 and blocked 5 to spend a holiday at the property with your family. The calendar automatically blocked another 2 for preparation time, which is the setting that blocks nights before or after each reservation to fit housekeeping. The other 5 remained empty.

Dividing the 18 sold by the 30 nights of the month, occupancy is 60%. Removing the family holiday, 25 nights remain for sale and occupancy becomes 72%. Also removing the 2 preparation nights, the denominator drops to 23 and occupancy rises to 78%. Nothing changed in the operation. Only the ruler changed.

There is a fourth version, for those who sell on more than one channel. The Airbnb help article on syncing calendars states that a reservation made on another site comes in as blocked on the Airbnb calendar. Suppose 6 of the 18 nights came through Booking.com. If the screen treats these nights as a block, as the wording suggests, the Airbnb dashboard sees 12 sold out of 17 free nights, or 71%. This is our reading of the published definition, not a formula confirmed by the platform. Check the blocked nights field on your screen before comparing.

The rule we recommend for your spreadsheet is simple and applies to any channel. An available night is every night of the period minus the ones you removed from sale by choice, such as personal use, renovations, or lending to a relative. Preparation time stays inside the denominator, because it is a consequence of your housekeeping policy and carries a cost. And a sold night counts as sold on any channel. In practice, what ruins historical tracking is switching criteria from one month to the next.

The same caution applies when peeking at competitors' calendars. A closed date could be a reservation, owner use, preparation time, or a night sold on another site. Market data from AirDNA, for example, excludes blocked nights from occupancy and uses a model with 16 signals to separate blocks from reservations. Counting by eye lacks this filter and tends to overestimate the neighbor's occupancy.

What is average daily rate (ADR) and what is left out of it?

Average daily rate, or ADR, is the nightly revenue for the period divided by the number of sold nights. If the 18 nights in the example yielded 4,140 u. in nightly rates, the average daily rate was 230 u.

The Airbnb dashboard calculates the average price per night by dividing the revenue from nights by the number of booked nights, and the published definition does not mention the cleaning fee. In your spreadsheet, leave cleaning out: it pays for housekeeping and varies with the number of stays, not the number of nights. AirDNA, however, includes the cleaning fee in the average daily rate. In the tool's own example, 5 nights at 250 u. with 200 u. in cleaning become an average daily rate of 290 u. Comparing your dashboard rate with a market tool's rate without this adjustment is comparing different things.

What about commission? To compare with the dashboard and the market, use the nightly rate before commission. The net amount is another calculation, done later, factoring in the Airbnb host fee, which varies by account and region, and applicable taxes.

What is RevPAR and why does it decide when occupancy and rate clash?

RevPAR is revenue per available night: the nightly revenue divided by the nights that were for sale. It is also equal to occupancy multiplied by the average daily rate, which is why it is the metric that arbitrates when one rises and the other falls. The acronym comes from the hotel industry, where RevPAR is published every month alongside occupancy and average daily rate. However, hotel and vacation rental occupancy metrics are not directly comparable due to owner blocks and platform differences. In a vacation rental, each night equals a hotel room, and the logic of the calculation is the same.

Now the case that matters to the host, in two 30-night months with no blocks, as an example. In month A you sold 27 nights at 200 u.: 90% occupancy, 5,400 u. revenue, and 180 u. RevPAR. In month B you sold 21 nights at 270 u.: 70% occupancy, 5,670 u. revenue, and 189 u. RevPAR. The less full month yielded more.

The chart shows the second effect. Each occupied night has its own cost: energy, water, amenity replacement, and wear and tear. At 25 u. per night, also an example value, B's advantage grows from 270 u. to 420 u. The percentage commission, on the other hand, does not change who wins, because it takes the same slice from both months.

How much does the nightly rate need to rise to offset falling occupancy?

To break even on RevPAR, the new nightly rate needs to be the current rate multiplied by the current occupancy, divided by the new occupancy. Starting from 90% at 200 u., dropping to 70% requires 257 u. just to break even. Anything above that is a gain. In practice, the curve bends upwards. Losing 10 occupancy points from 90% requires 25 u. more on the nightly rate; losing the next 10 requires 32 u. This is why the initial rule of thumb fails: 120 u. at 80% does not reach the 125 u. that would break even with 100 u. at 100%. The rule only wins when each occupied night costs more than 20 u., the point where the 6 fewer nights save the difference.

There is also a cost per stay, in addition to the cost per night, and hosts feel it on the calendar. One host shared in 2024 that she does not accept check-ins on the same day as a check-out, so housekeeping can be done calmly, and summarized the price of this: she loses at least one booking day. This is the preparation time that stays inside the denominator, and it grows along with the number of stays.

Every reservation brings a cleaning, a linen change, a check-in, and a round of questions about Wi-Fi passwords, parking, and check-out times. Filling the calendar with short, cheap stays multiplies all of this. The messaging part can be taken off your shoulders: Anfitrione answers repeated guest questions and sends check-in instructions on its own. Housekeeping, laundry, and wear and tear remain in your costs, and because of them, the fullest month is not always the most profitable month, even when gross revenue breaks even.

The reverse path applies to the low season. Lowering the nightly rate to fill up only pays off if occupancy rises more than the break-even ruler demands. Demand tactics for this are in the guide on how to fill your Airbnb in the low season.

Spreadsheet to calculate occupancy, ADR, and RevPAR

Copy the two tables into a spreadsheet. The numbers are from this guide's example month: 18 sold nights, 5 removed from sale by the owner, and 4,140 u. in nightly revenue.

In a spreadsheet with values A through E in cells B1 through B5, the formulas look like this:

Occupancy ........................... =B4/B3
Average daily rate .................. =B5/B4
RevPAR .............................. =B5/B3
Revenue per calendar night .......... =B5/B1

The last line deserves an explanation. RevPAR measures the operation, and therefore ignores the nights you chose not to sell. Revenue per calendar night is the revenue divided by all nights in the period, and measures the property as an investment. The 5 family holiday nights cost money, and it is this number, added up over the year, that you compare with a fixed long-term rental or with how much it costs to maintain the property. Both numbers are useful, each for a different question, and it is best not to swap one for the other.

What should you compare your occupancy rate with?

Compare with the same month of the previous year, then with the similar listings dashboard, and only lastly with market averages. Seasonality distorts comparisons between neighboring months.

One host shared in 2024 that he does not even look at the ready-made metric on the dashboard. He has fed a spreadsheet since 2019 and compares April with April, not April with March. That is how he saw January, February, and March 2024 close 17.88%, 13.93%, and 4.55% above the same months in 2023, and knew early on that April would not beat the record. He also noticed that costs rise from one year to the next, even when holidays are missing and revenue drops.

The detail that stands out in conversations among hosts is what gets left out. In a public exchange in 2024 about what the ideal occupancy rate would be, the numbers cited were 50%, 70%, 90%, and almost 100%. None came accompanied by the nightly rate. Another account, from 2026, celebrated 86% in a weak June after starting with a low price. Without the nightly rate, it is impossible to know if that month yielded more than the previous one.

When reading occupancy to adjust prices, compare it with local demand and lead time rather than treating any percentage as a universal target. RevPAR shows the gross-revenue trade-off; the final decision still needs costs and net income. And if what dropped was the number of reservations and not the nightly rate, the bottleneck might be earlier, in the listing funnel, which is the subject of the Airbnb performance dashboard.

The number that matters is what is left per night

The occupancy rate is the first number every host looks at and the most deceiving when it arrives alone. Always calculate it over the nights you put up for sale, using the same criteria every month. Next to it, note down the average daily rate and RevPAR. And before lowering the price to fill up, check the break-even line to see if the extra occupancy pays for the discount.

What pays the bills is the revenue per available night, minus the cost of each night and each stay. To carry this calculation through to the full year, the next step is to see if you can make a living from Airbnb with the numbers in your market.