Detecting interaction effects of concurrent experiments

Statsig introduces interaction effect detection to help medium to large companies accurately measure the impact of simultaneous A/B tests and uncover hidden interactions between experiments. While companies typically focus on measuring the "main effect" of each test, overlapping experiments can influence each other, leading to inaccurate results. Although studies suggest that interaction effects are rare, Statsig aims to enhance trust in experimental outcomes by detecting and managing these interactions. The feature uses statistical tests to identify interaction effects, as demonstrated in a scenario involving dark mode and transition animation experiments, where the combined effects led to a decrease in revenue and visits due to an antagonistic interaction. To address interactions, Statsig suggests isolating experiments, relaunching them to exclusive audiences, or reworking features for compatibility. This tool is designed to ensure trustworthy and efficient experimentation, and it is available on both Warehouse Native and Cloud platforms.