New Airbnb Occupancy Rankings Show Big Gaps Between Markets
A set of Airbnb occupancy rankings by country is making the rounds among hosts and property managers, purporting to show which markets are running hot and which are sitting empty. The headline claim is that occupancy varies sharply between established leisure destinations and newer, oversupplied markets. What the figures do not come with is a disclosed sample size, a date range, or an explanation of how occupancy was measured in the first place.
Where these figures actually come from
Airbnb does not publish official occupancy rates broken down by country. It never has. Any national or regional average currently in circulation has been modelled by a third-party analytics provider, typically by scraping public calendar availability across a sample of listings and inferring booked nights from blocked dates. That method can be reasonable at scale, but it conflates deliberate blackout dates, maintenance blocks and owner-use periods with actual bookings, and it says nothing about the rate those nights sold for. Treat any single country-level percentage as an estimate from one vendor's model, not a verified industry figure.
Why a national average tells an operator almost nothing
Occupancy inside any one country splits hard by city tier, property type and season. A national figure blends a saturated coastal strip with three-month peak demand against a rural interior running at a fraction of that rate all year, and hands back a number that describes neither. A two-bedroom apartment in a capital city competing against hundreds of comparable listings faces entirely different demand dynamics than a countryside cottage forty minutes away, even inside the same national boundary. Anyone using a country average to decide whether to add inventory, adjust rates or exit a market is working from a figure that was never built to answer that question.
What operators should track instead
The more useful number is the one sitting inside an operator's own booking system: occupancy against the specific comp set of similar properties within the same postcode or district, tracked month by month against the same period last year. Portfolio owners running multiple units across regions get more value from comparing their own properties against each other than from importing a scraped national figure with unknown error margins. Direct booking channels also give operators a cleaner read on demand than platform calendars alone, since they capture guests who never touch a marketplace listing; a direct booking website paired with calendar sync across OTAs gives a more complete occupancy picture than any single-platform export.
None of this means the broader trend behind the rankings is wrong. Demand genuinely is uneven across markets, and some destinations really are running fuller calendars than others this year. The problem is precision dressed up as fact. Operators reading a headline number that puts one country ten points ahead of another should ask which nights were counted, over what window, and by whom before it changes anything about how they price a Tuesday in March.
