How Airbnb Uses Analytics to Build Trust
This article is written by and republished with permission of Dr. Carla O’Dell, chairman for APQC.
Trust is the currency of today’s digital marketplace whether you are exchanging lodging or knowledge.
Imagine this: You are traveling to a foreign country for vacation and you are renting a home sight unseen from a person you have never met. Or (stranger danger alert!) you are letting a stranger use your home while you are gone. Before Airbnb, this would have been a rare and nail-biting transaction. Now we do it by the millions every year. Started by three guys just trying to pay their rent by putting air mattresses on their living room floor, Airbnb is now the largest and most valuable hospitality company in the world.
Airbnb’s business model relies getting hosts and guests to trust each other — and Airbnb. Trust can seem intangible until you realize it is established by reducing uncertainty and risk between the parties. That’s where Alok Gupta’s team of Airbnb’s data scientists comes in. Michael Sims and Carla interviewed Alok, data science manager at Airbnb, on the subject of trust, analytics and knowledge sharing. (Read Michael’s blog about the interview here.)
Alok and his team use the massive amounts of data generated through the Airbnb website to run experiments to learn how to build trust among strangers in their community of hosts and guests. What are the predictors of guest satisfaction? How likely is it that retired professional females will rent out a room in their house? (It turns out it is not rare.) How can we prevent bias? Recently, Airbnb mounted a campaign to promote inclusion and eliminate bias in hosts and guests, no small feat when ‘stranger danger’ is hard-wired into humans.
Just as he is passionate about data, Alok is also passionate about knowledge capture and transfer among his team of data scientists. He uses structured knowledge sharing and capture to avoid the wasteful practice of repeating experiments because no one remembers they were done. (Click Here for APQC’s Lessons Learned Overview.)
Even more importantly, he wants his team to capture and understand the decision process that was used around the experiment. In KM, the biggest complaint to capturing lessons learned is the time it takes. Alok has personally role modeled, required, and provided time for his team to engage in this knowledge capture and transfer.
