Airbnb headquarters in San Francisco. Emily Hagopian
Airbnb overhauled its logo, its website, and its mobile app this morning. But there’s something deeper going on with the sharing economy’s most popular travel site.
Under the covers, Airbnb has quietly begun an ambitious effort to painstakingly mine the treasure trove of data contained in the site’s customer reviews and host descriptions to create a smarter way of traveling. It turns outs Airbnb is more than a travel website—it’s a stealth big data company.
“For a long time now, Airbnb has been an awesome place to go if you know where you’re going and you know when you’re going,” says Mike Curtis, Airbnb’s vice president of engineering. “But we realized that we have all of this data that other people don’t have. We have travel patterns. We have the reviews. We have the descriptions of the listings. We know a lot about neighborhoods that we can infer from the text in there.”
To do this, the company has formed an eight-person Discovery team. Their mission? To build language processing software that mines Airbnb’s data and figures out what’s really happening out there in the travel world. In other words, Airbnb is building a kind of omniscient, machine-powered travel agent of the future.
‘We realized that we have all of this data that other people don’t have. We have travel patterns, we have the reviews, we have the descriptions of the listings.’
You can see the early hints of this in the new recommendations that debut on the site today. Airbnb figures out where you’re from, and then drops you a few travel ideas. “We try to figure out exactly where you are and who the people are around you and where they like to travel,” says Surabhi Gupta, an engineer on the Discovery team.
If you’re booking from Knoxville, Tennessee, for example, there’s a pretty good chance you’ll want to take in the sights in Washington, DC. If you’re from the San Francisco or Brooklyn, you may very well be looking for a booking in the same city (folks in these places are more likely to be using Airbnb to book accommodations for friends or relatives).
Airbnb’s Discovery team, from left: Phillippe Siclait, Nasseem Hakim, Frank Lin, Gauri Manglik, Surabhi Gupta, Lu Cheng Airbnb
The Discovery team figures this out by extracting interesting words from the site’s reviews and descriptions. An open-source tool called the Stanford Part of Speech Tagger comes in handy for this. It then uses custom-build algorithms to assign 150 different attributes—beaches, hiking, sunsets, and so on—to different locations.
What you see on the homepage is a start, but Airbnb wants to get to the point where it can give very specific recommendations based on who you are, not just where you live. “A lot of what we’re doing is the foundational work for user-level personalization,” says Lu Cheng, another Discovery team engineer. That means, in a few years, you may very well be using Airbnb to not only book your next vacation, but to figure out where the heck you want to go.
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