The point is that if your metrics are not stationary, then the variance in observations will seem higher than they really are if you don't account for time. Thi

The point is that if your metrics are not stationary, then the variance in observations will seem higher than they really are if you don't account for time. This means you have to collect a lot more data before being able to draw a statistically strong conclusion. They describe a way of adding a time based stratification to the experiment data that doesn't have the weaknesses of simpler methods, like stratifying using a fixed interval size (like day)