How Airbnb uses location data to improve guest satisfaction
A glance at how “location” is such an important aspect in the hospitality industry
What Americanos and Espresso are to Starbucks, New York, and Paris are to Airbnb. Airbnb made an entry into the hospitality sector of the “sharing economy” by arranging/offering a homestay or local experiences for guests. Airbnb is a community marketplace for extra spaces where people having an extra space host and those traveling to those areas book those homes.
Airbnb was born out of necessity. Our rent kept going up. It was born out of a problem. ~ Jeo Gebbia, Co-founder
If you are someone who loves to crunch numbers, you will be amazed to know that Airbnb has more than 3 million listings with 650,000 hosts in over 191 countries. Due to some forces affecting tourism, it is most popular in the United States, France, Italy, Spain, and the United Kingdom, but travelers can find listings (stays/experiences ) in 98% of the world’s nations.
Let’s have a look at how Airbnb leverages location data for scaling its business and to offer better customer experience.
Location Relevance
How many of us know about Bir Billing?
I myself recently found out about that very recently. A small, yet exquisite village in Himachal Pradesh, Bir is well known for its monasteries and paragliding/trekking activities.
Airbnb bridges these gaps by creatively helping people find the “local” experience they are looking for in places we know very little about. Their search algorithm which combines various signals to list out the experiences guests want to have or the places they want to visit plays a crucial role in this.
To make their search and listing more precise, Airbnb used something known as “listing quality score” to list out places according to proximity to the center of search and guest reviews. It is interesting to note how Airbnb used the voice of their guests to come up with a conditional probability of booking in a location given where the user searched for. [Source]
For example , a search for Clyde Hill in Washington would thus slide towards neighborhoods where people who also search for Clyde Hill typically wind up booking, for example the Yarrow Point or Evergreen Point .
Better Search Ranking
The factors which determine how the various places or experiences are listed on Airbnb have a high correlation with location data. The search ranking algorithm helps guests find the perfect listing for their trip and hosts find guests who are a great fit for their place. Airbnb has been getting the real estate economics right by adjusting a few signals like smart pricing, visibility, and conversion trigger.
When a listing/place is in a high demand area, then they can benefit from late-stage visibility (i.e your place may appear in search results because all other listings are booked). A good location and a proper optimization of risk preferences can turn out to be advantageous for your stay taking ranking factor into consideration.
Smart Pricing
A large chunk of Airbnb hosts view the site as a supplementary income and not their main gig. 80% of the hosts rent just a room in their home, a guest house or a vacation home. Airbnb has a surprisingly positive impact on local economies since their guests stay 2.4 times longer, they spend 2.3 times more money than hotel guests and this earning stays within the closely bound neighborhood.
An official video by Airbnb which shows how smart pricing actually works:
The overall profitability of the host (and Airbnb) depends on factors like the time a host can invest, prior market knowledge and relative responsiveness to changing patterns and shifts in demand with respect to the seasonality. To fight this problem of changing prices, Airbnb came up with a game-changing solution known as smart pricing which used predictive analytics to come up with optimal rates for any given day.
This feature changes the booking price as per real-time changing conditions.
Many of the factors affecting smart pricing have a geospatial component. Factors like the location of the stay, proximity to public transit, season and amenities available in an area affect the pricing and booking.
Building Trust
Trust is the fundamental currency of the “sharing economy” and is at the heart of almost everything that we do. Airbnb is building trust for its community by offering three things: safety, transparency, and support.
It is interesting to note how technology plays the role of a lever in ensuring trust among hosts and guests. A combination of predictive analytics and behavioral analytics is used to assess the risk of every listing. The risk could be in terms of location or any previous suspicious activity in the homestay/place. To avoid such cases Airbnb runs many background checks on its guests and hosts to make sure that none of them have any previous records of any kind of criminal offense.
Brian Chesky highlights the importance of trust in a sharing economy. In his own words,
I’m not saying the whole world will work this way, but with Airbnb, people are sleeping in other people’s homes and other people’s beds. So there’s a level of trust necessary to participate that’s different from an eBay or Facebook .
Airbnb for Work gives the travel managers of each registered company a dashboard to keep track of their employees while they are spread across the globe. They can have complete visibility about where each person is currently traveling and will be traveling in the future.
Joe Gebbia in this TED talk speaks about how they overcame the stranger-danger bias and designed a platform to build trust among the community members.
It is a psychological trait among humans that we trust people who show a high degree of similarity with us be it in terms of age, location or geography. As per this case study on Airbnb by Standford University, people (hosts/guests) with diverse demographics backgrounds tend to trust each other only if each of them has good reviews in the past.
Airbnb Maps
People usually find it hard to believe that cartographers at Airbnb are busy mapping the world. Wait, what? Isn’t the world already mapped by Google Maps, Waze, Foursquare (to name a few)? This isn’t false but Airbnb set themselves out on a journey to solve big questions and hard problems by mapping locations on the world to find their relationship with other locations.
With Airbnb Maps, you can track real-time activity at an Airbnb located in any part of the world. Sitting in your room you could actually see someone flying over Australia’s Great Barrier Reef or someone checking in at an exotic homestay Airbnb in Italy or maybe see someone having authentic local experiences in Paris.
There are culturally significant areas or regions that aren’t drawn on maps. They mostly live in the minds of the local community that calls those areas home. Airbnb puts effort in finding and mapping these places so that you know where in the world should you travel so that it makes a perfect trip for you and your loved ones!
Improving Sustainable Tourism
The Healthy Travel and Healthy Destination report show that Airbnb through its platform and community model helps fight mass tourism and promotes sustainable tourism.
Airbnbs encourage geographic diversity and the proper distribution of the guest to avoid over-tourism. Majority guest arrivals at well-known global tourist destinations take place outside of traditional tourist areas, and 72 to 93 percent of Airbnb listings are located outside of areas that are at risk for over-tourism. This ensures that homestays are less concentrated as compared to hotels and results in a homogenous dispersal of guests
Not only that, tourist perceptions about different parts of the city largely affect the inflow of tourists to a particular place/location. A combination of guest reviews and ratings helps people decide on their next homestay/experience.
Host and Guest Acceptance
Airbnb puts a lot of effort to make sure that hosts are equally benefitted. They make it possible by architecting better matching algorithms so it results in an increase in booking conversion.
For each search query that a guest enters on Airbnb’s search engine, their model computes the likelihood that relevant hosts will want to accommodate the guest’s request (as per official data, this resulted in about a 3.75% increase in booking conversion) and it is safe to say that location plays a very critical role in that!
Read More:
Hope you liked this piece. You can read similar applications of location data here:
How do On-Demand Food Delivery Companies use Geospatial Data
How does Uber do Surge Pricing using Location Data
Hi! I am a final year CS undergrad at KIIT University, passionate about data science, economics, climate change , growth hacking and starting up. I love to read anything and everything I lay my eyes and cursor on! You can reach out to me on LinkedIn or Twitter.
