Occupancy rate is calculated by dividing the number of reserved days by the total number of available days in the month for a property. Listings with no reservations are excluded.
Reserved Days / Total Available Days
When calculating occupancy for a short-term rental, it’s essential to consider the number of days the property was available, as not all listings will be available year-round. For example, a listing could have been available 150 days of the last 12 months and occupied 50% of the time, so it was occupied 75 days in total.
A high occupancy rate isn’t always a good thing; it may have a negative effect on revenue as the host may be charging a nightly rate that is too low, in turn receiving a high number of reservations but having an adverse impact on the revenue generated. Having the property occupied consistently can also pose challenges for cleaning, maintenance, and guest changeover.
Optimizing your occupancy rate is about working out a balance between a good rate for both the host and the guests. Learn more about how to strike the perfect occupancy rate balance.
How do you take into account that a property might be advertised in other platforms than the ones you scrape and therefore occupancy rates might not be the real occupancy rates of the property? So as a simple example, a property with 100% real occupancy rate being advertised on Airbnb and Booking, receiving 50% of reservations from each, would we see a 50% occupancy rate on Airdna?
Hi Borja, when scraping the listing's calendar, our algorithm can determine whether an unavailable date has been blocked by the host or is a genuine booking. In your example, if the listing had been reserved through Booking, by scraping the Airbnb calendar, we can see that the listing is unavailable and would then apply the logic of our algorithm to determine whether it is a booking or not.
We then take the rate the booking was priced on Airbnb to work out the total revenue for the booked dates.
How exactly can the algorithm tell whether the booking has been blocked by the host or is a genuine booking? Are some assumptions made? This is not data made available by Airbnb.
We began scraping data from Airbnb in 2014, at which point they stated whether a listing was booked, available, or blocked by the host in the listing calendar. As you say, this information is no longer available from Airbnb, but our algorithm works off the same logic now as it did then to determine the availability of a listing.
Thanks Tom, for the quick response. Could just clarify how the current logic works then? How exactly does AirDNA determine when a listing is booked vs made unavailable by the host?
Hi Alexander, I’m afraid I can’t tell you exactly how we determine booked days vs. blocked days, but it is based upon 16 different booking signals, such as the length of stay and how far in advance the booking is made. You can read more about our data methodology here.