Experimentation and Startup Performance: Evidence from A/B Testing

Recent scholarship has argued that experimentation should be the organizing principle for entrepreneurial strategy. Experimentation leads to organizational learning, which drives improvements in firm performance. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of testing business ideas. Our results provide the first evidence on how digital experimentation affects a large sample of high-technology startups using data that tracks their growth, technology use, and products. We find that while relatively few firms adopt A/B testing, among those that do, performance improves by 30% to 100% after a year of use. We then argue that this substantial effect and relatively low adoption rate arises because startups do not only test one-off incremental changes but also use A/B testing as part of a broader strategy of experimentation. Qualitative insights and additional quantitative analyses show that experimentation improves organizational learning, which helps startups develop more new products, identify and scale promising ideas, and fail faster when they receive negative signals. These findings inform the literatures on entrepreneurial strategy, organizational learning, and data-driven decision-making.