(Bloomberg) -- Airbnb Inc. is prohibiting some users from booking single-night rentals of entire properties as part of the home sharing platform’s push to prevent parties on New Year’s Eve.
The company will ban the reservations for guests without a positive account history or previous bookings on the platform, factors that it sees as likely for a party to occur, according to a statement Thursday. A booking in the same area where a guest lives will also raise a a red flag. And, if the same guest tries to book a two- or three-night reservation, Airbnb will suggest they book a private room or hotel. The restrictions will take effect over the upcoming New Year’s Eve weekend in 11 countries, including the US, Canada, Brazil, France, Spain and the UK.
The moves follow Airbnb’s formal codification of a party ban in the summer, which began as a public health measure in the early days of the pandemic. The company will introduce reservation screening technology globally next year to help boost trust and safety between hosts and guests amid an expectation that more people will become hosts to bring in a second source of income as the economy slows.
“If you have a positive history and you’ve been a booker and you planned a trip in advance, those types of trips are pretty safe,” Naba Banerjee, director of trust product and operations at the San Francisco-based company, said in an interview. “If the host is present the chances of you throwing a rager are minimal.”
The new reservation screening features will use context clues, like a newly created account, a user’s booking location and age to determine if they may be trying to host a party. The company piloted a test of the New Year’s Eve restrictions in eight countries last year and said that 340,000 guests were blocked or redirected from a booking over the holiday. Airbnb estimates that the restrictions led to a 56% drop in the rate of party incidents during the holiday last year compared with 2020.
Machine learning is helpful in preventing parties when hard and fast rules can be too blunt given the size of Airbnb’s community, Banerjee said. “At this scale what we’re learning is rules don’t scale and rules are too blunt,” she said. “Our models are trying to learn with the data that we have.”
©2022 Bloomberg L.P.