Design Features of Airbnb

Price tips

Based on data from millions of stays Airbnb developed tool help determine price in order to increase the likelihood of bookings. Using algorithm from machine learning Airbnb provides pricing for everyday of the year. There are user friendly features hosts can look at to see if dates are in green which indicates a high likelihood of booking and a red which recommends a change in price. This feature which can be coded through python using data can capture value from higher booking rates.

Improving Search Result

In continuous process to improve search results for guests, Airbnb dove into data to create solutions of algorithmically challenging issue. The main challenge was factoring in user preferences alongside geographical proximity. Through series of complex tests, Airbnb's final algorithm combined user behavior data using statistical models and data visualization, to produce more location relevant result for users. Model has made it easier for companies to apply cities across the world rather than map out individual cities purely based on proximity from city centers which is not always where a guest might want to be.

Understating Host Acceptance Decision

To maximize the guest user experience Airbnb needed to maximize likelihood that a stay request would be accepted by host, therefore allowing Airbnb to invest on creating better matching algorithms. As a matter of fact, Airbnb used the results of experiments to influence guests search result by ranking host properties with higher likelihood of acceptance higher.