The most important part of this article is the way that Gelman derives the value. He writes a simple R script to simulate the outcomes. Many, many introductory stats classes will teach you a variety of formulas to estimate the "statistical power" of various experiments, and it's easy to get intimidated and worry if you know the right one to use. But if you know how to program, and you have a reasonable set of assumptions you'd like to test, then you can do a similar analysis in about 10 minutes. These analyses can often save you months of work when you figure out that your exciting study idea has no hope of detecting a difference or that you actually don't need 10000 subjects to detect a 10% lift in conversion rate. Thank you, Professor Gelman!