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December 21

AI Tackles Anti-Social Tenants: Airbnb’s Holiday Strategy

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The rising popularity of serviced apartments attracts guests seeking hotel-like comforts while maintaining their privacy. To stand out among the competition and increase profitability, it’s crucial to enhance your marketing strategies for your multiple properties in town.

Airbnb in the UK is taking proactive steps to curb disruptive parties during the New Year’s Eve celebrations. To achieve this, the platform is leveraging proprietary anti-party Artificial Intelligence and machine learning technology. This advanced system is designed to analyze booking attempts for entire home listings over the holiday weekend, particularly focusing on one, two, and three-night stays that may pose a higher risk of hosting disruptive and unauthorized parties.

 

By employing this technology, Airbnb aims to identify and block bookings that could potentially lead to anti-social incidents, fostering a more secure environment for hosts and their neighbors. This move is part of the platform’s commitment to responsible hosting and ensuring a positive experience for both guests and local communities. As the holiday season approaches, these measures seek to strike a balance between offering accommodations and preventing disturbances associated with unregulated gatherings.

 

Hosts on Airbnb can expect increased support from these technological interventions, which align with the company’s broader strategy to address concerns related to unauthorized parties and maintain the platform’s integrity. The implementation of such advanced tools reflects Airbnb’s commitment to adapting and utilizing technology responsibly to enhance the safety and well-being of its users and the communities they inhabit.

 

Airbnb, in its commitment to responsible hosting and community welfare, has implemented sophisticated technology to assess various signals indicating a higher risk of disruptive incidents during bookings. This proprietary system scrutinizes factors such as the duration of a guest’s trip, the proximity of the listing to their location, the type of listing booked, and the timing of last-minute reservations. By analyzing hundreds of signals, Airbnb aims to identify patterns that may suggest a heightened likelihood of hosting disruptive parties or unauthorized events over the holiday season.

 

Naba Banerjee, Head of Trust and Safety at Airbnb, emphasizes a thoughtful and purposeful approach to the utilization of technology like AI. The primary focus is on providing tangible benefits to hosts, guests, and the surrounding communities. By incorporating these advanced measures, Airbnb seeks to contribute positively to the areas it serves, ensuring a more secure and enjoyable experience for everyone involved. This strategic implementation of technology not only aligns with Airbnb’s commitment to responsible hosting but also underscores its dedication to fostering safer and more harmonious neighborhoods during festive periods and beyond.

 

The measures will see:

  • Restrictions on one-three night reservations – Our AI technology will block certain one – three night entire home bookings identified as potentially higher-risk for a party incident;
  • Mandatory anti-party attestation – Guests able to make local reservations will need to attest they understand Airbnb bans parties and that if they break this rule they face suspension or removal from the platform.

Airbnb brought in anti-party measures last New Years Eve that saw thousands of people globally blocked from booking an entire home listing on the platform, including approximately 13,200 people in the UK, 63,550 in the United States, and 5,400 in Australia. 

Moreover, since first introducing party prevention measures for New Year’s Eve in 2020, the short lets platform has seen a 73 per cent reduction in the rate of party reports made to us in the UK over this holiday.

In the UK, approximately 13,200 guests were blocked or redirected from attempting to book on Airbnb over New Year’s Eve. This includes approximately 3,300 in London, 2,100 in Manchester, 380 in Birmingham and 260 in Edinburgh. 

The measures include reservation screening, a noise sensor for hosts, and helplines for neighbourhoods and hosts.

 

Read more Property Investing News HERE

 


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AI, AI Tackles Anti-Social Tenants: Airbnb's Holiday Strategy, AirBnb, Anti Social Behavior


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