Explore advanced causal inference techniques in this 35-minute conference talk from the Data Science Festival. Delve into the world of estimating action impacts, a powerful analytical approach gaining recent attention. Learn how causal inference differs from classic supervised machine learning and why specialized techniques are necessary. Discover the auto-causality package, which leverages open-source libraries from Microsoft to automate model selection and result visualization. Follow along as the speaker demonstrates a practical application of auto-causality in analyzing real A/B test results from Wise's feature testing and CRM campaigns. Gain insights into measuring not just average impact, but also understanding which customers respond better to different options.