It is interesting to see the math behind why it did not works and probably it is a good approach to never discard an idea just because it sounds stupid. But I see really a little value in this line of thinking.<p>One of the big issues with experiments is how much value they really drive, which is the real effects. In many situations we do A&#x2F;B testing for changes whose real impact is a fraction of a percent of the tracked metric. If anyone followed the discussion about p-hacking in science [1] should really start wondering if the way we run experiments, considering the little changes we see, is not nearing p-hacking, especially when I see this ideas floating, and if we don&#x27;t need to find more significant way of running our experiments.<p>[1] One of the first article I found about the issue <a href="http:&#x2F;&#x2F;journals.plos.org&#x2F;plosbiology&#x2F;article?id=10.1371&#x2F;journal.pbio.1002106" rel="nofollow">http:&#x2F;&#x2F;journals.plos.org&#x2F;plosbiology&#x2F;article?id=10.1371&#x2F;jour...</a>