I was hoping for more hard science and statistics in this book – it did provide a large number of numerical facts, but the conclusions seemed a bit rushed and unconvincing at some points. Furthermore, I couldn't shake the feeling that the book was actually written in 2013-ish when Big Data and A/B Testing were all the rage and were going to change everything – in 2017 it somehow manages to feel already dated. Big data is no longer the prime buzzword and we already know that excessive A/B testing leads to a number of other problems (like fake news, for example).