Chiraag Kala - Rethinking A/B Tests for Connected Users and Teams

For information on upcoming conferences, visit https://www.dataconf.ai. Rethinking A/B Tests for Connected Users and Teams by Chiraag Kala Abstract: Imagine running experiments that assume everyone acts independently—only to realize that, in practice, people collaborate. On platforms like Airbnb, for example, hosts can partner with other co-hosts, forming networks where behavior is interdependent. Traditional A/B tests that randomize individuals ignore these relationships, leading to biased results. In this talk, we introduce a new experimentation design that treats entire teams or networks as the unit of analysis. By accounting for collaboration and spillover effects, this approach yields more accurate results and leads to a better user experience. Whether you're building an e-commerce platform, a social network, or a financial product where users operate in groups, network-aware experiments will help you make smarter, more reliable decisions. Bio: Chiraag is a Lead Data Scientist at Airbnb who researches and develops novel experimentation methodologies for marketplaces. He designs and runs experiments and develops models that transform data into clear insights. His work not only enhances the user experience on the platform, but also drives innovation across the entire platform. Presented at The New York Data Science & AI Conference Presented by Lander Analytics (August 27, 2025) Hosted by Lander Analytics (https://www.landeranalytics.com)