In A/B testing, the more comparisons you make, the higher the chance of finding a statistically significant difference purely by chance. For example, if you are running five tests simultaneously, and you are using a significance level of 0.05 for each test, the probability of making at least one Type I error is not 0.05 but rather closer to 0.23. This is where FWER becomes a critical consideration.