A/B Testing at Scale: Accelerating Software Innovation

The Internet and the general digitalization of products and operations provides an unprecedented opportunity to accelerate innovation while applying a rigorous and trustworthy methodology for supporting key product decisions. Developers of connected software, including web sites, applications, and devices, can now evaluate ideas quickly and accurately using controlled experiments, also known as A/B tests. From front-end user-interface changes to backend algorithms, from search engines (e.g., Google, Bing, Yahoo!) to retailers (e.g., Amazon, eBay, Etsy) to social networking services (e.g., Facebook, LinkedIn, Twitter) to travel services (e.g., Expedia, Airbnb, Booking.com) to many startups, online controlled experiments are now utilized to make data-driven decisions at a wide range of companies. The theory of a controlled experiment is simple, but for the practitioner the deployment and evaluation of online controlled experiments at scale (100’s of concurrently running experiments) across a variety of web sites, mobile apps, and desktop applications presents many pitfalls and new research challenges. In this tutorial, we will introduce the overall A/B testing methodology, walkthrough use cases using real examples, and then focus on practical and research challenges in scaling experimentation. We will share key lessons learned from scaling experimentation at Microsoft to thousands of experiments per year and outline promising directions for future work.