We thank the reviewers for the constructive feedback and are happy to provide clarifications. We would like to stress the benefit of this work. The counterfactual policy evaluation is useful in two ways. Due to the space constraint of this letter, we answer three of Reviewer 3's broader questions. Reviewer 3 asks about extensions to cyclic graphs.

A/B tests are a crucial tool for evaluating experiments in marketing domain. It is performed by subjecting different population samples to variations of an offer. The results are observed at the end of experiment to select the best performing variant. Marketing teams need to spend a lot of time in crafting these experiments. It also takes time and money to wait for results to iterate and improve.