Against A/B tests

December 12, 2018 - 1 minute read -
a-b-testing data science reblog statistics blog

Traditional A/B testsing rests on a fundamentally flawed premise. Most of the time, version A will be better for some subgroups, and version B will be better for others. Choosing either A or B is inherentlyinferior to choosing a targeted mix of A and B.

Michael Kaminsky locallyoptimistic.com

The quote above is from a post by Michael Kaminsky “Against A/B tests”. I’m still not fully convinced by Michael’s thesis but it is very interesting and thought-provoking.