Airbnb's recommendation systems

Airbnb uses "recommendation" systems to help guests discover destinations, homes, experiences, or services and other content that may be of interest to them.

A recommendation system is an automated algorithm that influences the selection, display and ranking of information on our platform. The content recommendation systems we use may evolve over time. They include:

• The automatically displayed accommodations, experiences and services listings that you see when you visit our homepage;
• Our search functionality, which you can use to search for listings according to criteria that you set - find out more about how search results work;
• Suggested destinations, which suggests inspiring destinations you may want to consider for your next trip;
• Our default ranking of reviews, which displays reviews based on their likely relevance to you.

The recommendation systems we use provide recommendations based on one or more of the following factors.

• Your location
• Your language settings
• Your browsing history on Airbnb, including past searches and bookings you’ve made on Airbnb
• Searches and bookings made by users who have a similar profile to you
• The time of year and seasonality (for example, the listings you see on our homepage may differ depending on whether you’re searching in the winter or the summer)
• The location of a listing and where relevant, its proximity to your location or the location of your booked accommodation
• The quality of a listing (including the listing’s characteristics, user ratings and reviews, and other factors)
• Listing price
• Listing popularity (determined by how users interact with the listing)
• Listing availability
• How far in advance you’re looking to book
• Your trip duration
• Your booking party (number of guests and type of guest)
• The language, length and recency of a review.

To help make it as easy as possible for you to find and book accommodations, experiences and services that are more likely to appeal to you, the amount of weight that our recommendation systems place on each of the factors they use to display content to you may vary.