At Airbnb, we are constantly iterating on the user experience and product features. This can include changes to the look and feel of the website or native apps, optimizations for our smart pricing and search ranking algorithms, or even targeting the right content and timing for our email campaigns. For the majority of this work, we leverage our internal A/B Testing platform, the Experimentation Reporting Framework (ERF), to validate our hypotheses and quantify the impact of our work. Read about the basics of ERF and our philosophy on interpreting experiments.
At Airbnb we are always trying to learn more about our users and improve their experience on the site. Much of that learning and improvement comes through the deployment of controlled experiments. If you haven’t already read our other post about experimentation I highly recommend you do it, but I will summarize the two main points: (1) running controlled experiments is the best way to learn about your users, and (2) there are a lot of pitfalls when running experiments. To that end, we built a tool to make running experiments easier by hiding all the pitfalls and automating the analytical heavy lifting.