![]() We look at 16 different booking signals, such as the length of stay, lead times, reviews, and more, to produce accurate booking performance for individual listings and whole markets.Think of it like this if you have a rental property in Las Vegas, without software, all you can do is look at similar listings and maybe factor in some seasonality to come up with a price, right? To do this, AirDNA has developed advanced artificial intelligence and machine learning technology to identify blocks and unavailable days on Airbnb and VRBO. When we look at listing performance, we need to ensure that we count booked days and not blocked days as revenue generators. The days the host has blocked will show as unavailable in the listing calendar, just as a booking would. In the below example, the listing was available to be booked 320 days of the possible 365 days over the last 12 months and occupied (or booked) 52% of those available 320 days, therefore blocked by the host for 45 days. They may do this for several reasons, for example, if they want to use the property themselves or due to STR regulations in their market. ![]() Many hosts choose not to list their STR full-time and will block days off in the listing calendar. ![]() At AirDNA, we only look at the occupancy rate of a listing when it is available to be booked, as this gives the most accurate reflection of booking performance. When analyzing short-term rental (STR) occupancy rates, it is crucial to understand listing availability.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |