Loops announces $14 Million funding round! 🎉

The False Sense of Confidence With “Before-After” Analysis

In this article, Iyar Lin, data science lead at Loops, goes through the “behind the scenes” of one of our most used types of analyses: Release Impact. A/B tests are the gold standard for estimating causal effects in product analysis. But in many cases, they aren’t feasible. In this post, I’d like to discuss one […]

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