We have a dataset containing: customer features, A/B test version and whether the customer placed an order or not.We'd like to discover groups of customer features that were most impacted by a given A/B test from a conversion (placed an order or not) perspective. E.g. We've noticed a high conversion drop in customers from Alabama coming from Google in version B (because customers from Alabama coming from Google had worse conversion rates in version B compare to version A).Any direction on how to model this problem and which machine learning algorithm to use is appreciated.Thanks!
Customer features more impacted by A/B tests
machine learning;unsupervised learning