Directionally useful, precisely wrong. AirDNA infers occupancy and revenue from calendar signals it cannot see behind, so a blocked night and a booked night look alike. Hosts on r/AirBnB report estimates landing 20–40% off their own books, with dense urban ZIPs closer and rural markets worst.
AirDNA scrapes public listing calendars and reads unavailable nights as sold nights. From that it derives occupancy, then multiplies by a scraped asking price to get revenue. No part of that chain sees a booking confirmation, a payout, or a rate a guest actually paid.
That is not sloppiness. Platforms do not publish booked data. Every market-intelligence product in this category is modelling the same blind spot — the honest question is how large the error is for your listing, not whether it exists.
Paraphrased from recurring threads on r/AirBnB and r/airbnb_hosts. The pattern is consistent: useful for ranking markets, unreliable for underwriting a single property. — the same split our full AirDNA review lands on.
We do not model occupancy at all. We read asking prices off live listings, night by night, and show you the spread. Fewer claims, and every one of them checkable.