Active Listing: A listing that has an active page on
Airbnb or had one at some point in the last 15 days.
Bedroom Category: By default listings in the Market
Dashboard are grouped by the number of bedrooms they advertise on Airbnb. In
addition, there is a “Room” category that groups all listings with 0 or 1
bedroom that is advertising as a shared, private, or hotel room.
Booked Dates: This refers to a time period where we
consider the bookings that were received, whether or not the stay dates for
those bookings have occurred yet. For example, “Past 30 Booked Dates” can be
read as “for bookings received in the last 30 days”.
Booked Nightly/Weekly/Monthly Price: The price per
night for bookings that have a certain length of stay. Booked Nightly Price
would consider all bookings, Booked Weekly Price would consider bookings with
length of stay greater than or equal to 7, Booked Monthly Price would consider
bookings with length of stay greater than 30. Length of Stay discounts are
Booking Window: The number of days between when the
booking was made and the first stay date for that booking. A same day booking,
where the first stay date is the same as the booked date, would have a Booking
Window of 0. If someone books today to start their stay tomorrow that would be
a Booking Window of 1. Etc.
Length of Stay (LOS): The number of nights a booking
is for. For a booking where guests check in Friday and checkout Sunday the
Length of Stay would be 2 (Friday night and Saturday night)
Percentile: The percentage of listings that fall at
or below the given value. For example, if the 25th percentile price
is $144, that means 25% of listings have a price equal to or lower than $144.
Scraped Data: Data that comes from publicly viewable
websites and pages. For listings some examples of data that we scrape are
future prices, future available dates, listing info such as number of bedrooms
and amenities included. See Data Source and Processing section for more details
on the data we gather and how we process it.
Stay Dates: This refers to a time period where we consider bookings where guests have stayed at the listing during the period. “Past 30 Stay Dates” can be read as “In the past 30 days for bookings where guests have stayed”.
Currently Market Dashboards is using only scraped data from Airbnb. For a listing all data we gather could be found by going to that listing’s public Airbnb page and looking through their calendar and the listing info they provide. We then keep records of how their calendar has changed, what dates have become unavailable (or re-available), how their prices have changed, etc. and we build up a history for that listing. We currently do this for all listings that appear on Airbnb. Using scraped data enables us to provide Market Dashboards for any location around the world (regardless of whether we have customers there or not).
One of the main challenges for scraped data is that there is no guaranteed way of determining if specific dates are not available because they were booked or if the owner has decided to block those dates. Everyone using scraped data faces this issue and generally has some way in which to try and remove these blocked dates from the data, and no method is perfect. PriceLabs has its own block removal logic that looks at patterns in the whole market as while as individual listing data to help us determine whether a booking is real or a block. Some of the factors of a booking we look at to determine if it is a block or not are: Length of Stay, Booking Window, Market Occupancy, extreme Price variations, and more. We also automatically remove any stay greater than 60 days as we feel they do not fall under the Short-Term Rental category and can have a large impact on the data. Once a block has been found the corresponding dates for that listing are changed to available and do still count as the listing being empty when calculating market level Occupancy for those dates. All other booking info is also removed.