How Airbnb Uses Machine Learning to Enhance the Customer Experience

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With over 6 million active listings spanning thousands of cities worldwide, Airbnb connects a highly diverse array of hosts and travelers. To help deliver personalized booking experiences at scale, Airbnb uses AI across its suite of products.

Keep reading to learn the key ways this $100 billion tech disruptor leverages machine learning (ML) to power its impressive business growth.

Airbnb Machine Learning Image Classification Helps Maximize Bookings

Listings on Airbnb contain over 500 million customer images, making it the world’s largest collection of home and property photos. As visuals carry significant influence in securing bookings, properly categorizing these images was critical to growth.

But one of Airbnb’s biggest problems was how Airbnb hosts mislabeled and ordered their images. For example, a host might accidentally upload a picture of their backyard and label it as their kitchen. Hosts also didn’t always make their best photo the featured photo for their Airbnb listing.

To solve these issues, Airbnb utilized the image classification neural network ResNet 50 to rapidly classify millions of photos by room type and visual appeal. This enabled optimized display of a host’s best images when customers browse Airbnb listings. By clearing up mislabeled images with ML and showcasing the most attractive photos in a data-driven manner, Airbnb bookings increased substantially.

Airbnb is now working on using machine learning to detect specific objects and amenities within images. If a user filters searches by amenity type, then relevant listings based on these advanced classifications will be displayed.

Personalized Ranking of Airbnb Experiences Listings

Beyond just homes, Airbnb Experiences connects travelers with unique local activities like cooking classes, sightseeing tours, and more. With thousands of global Airbnb Experiences listings being added to the platform monthly, developing an effective search ranking model to improve search and discoverability was crucial.

Airbnb built a machine learning ranking algorithm using their platform data including impressions, listing clicks, and confirmed bookings. The model weights many signals – host location, number of guests, price, availability, etc – to determine relevance. It further customizes results by travelers’ country of origin based on observed activity patterns. Adding to the data pool, most Airbnb Experience customers also book an Airbnb too.

This personalized ML approach means a husband and wife booking an Airbnb in Paris will see intimate couple experiences ranked higher in their search results, not group activities better suited for families or large groups. The model improves continuously as more behavioral data is collected from the Airbnb Experiences platform.

Extensive Usage Across Platform & Infrastructure

While the listing search/discovery use cases exhibit Airbnb’s public-facing ML, the company uses machine learning across their entire tech stack. Airbnb has already operationalized hundreds of ML models, leveraging open source frameworks like TensorFlow for rapid development and deployment.

A few examples:

• Predictive analytics guides pricing and capacity planning for listings to balance supply and demand
• Matching algorithms pair ideal listings with travelers based on interests, history, and trip purpose
• Image recognition will eventually classify property attributes at scale to enable enhanced amenities filtering

How Airbnb’s Machine Learning Platform Powers Their Growth

As one of the travel industry’s most innovative companies, Airbnb will continue leading the industry’s AI revolution. With their tech stack already built data-first to capitalize on ML, enhancing personalization and accurately forecasting demand is now table stakes.

The the future, Airbnb will have an opportunity to expand usage across trust and safety, fraud detection, dynamic automated pricing, and beyond.

From maximizing bookings with properly classified images to ultra-personalized Experiences recommendations, Airbnb’s commitment to ML has been central to their success.

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