The A/B test (also known as a randomized controlled trial, or RCT, in the other sciences) is a powerful tool for product development.
As well as being perhaps the most accurate tool for estimating effect size (and therefore ROI), it is also able to provide us with causality, a very elusive thing in data science! With causality we can finally lay to rest the "correlation vs causation" argument, and prove that our new product actually works.
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