A few posts back, I examined a simple technique for using an exponential moving average (“EMA”) on your time-series metrics. This has the advantage of smoothing out the metrics while at the same time keeping a “memory” of all previous values of the metric that came before. It also has the side benefit of being easier to update as new values to your metrics come available.
This time, I want to show you a technique to fix another common time-series problem: seasonality. Yeah, your metrics are down in January, but is that the usual post-holiday sales slump? Or is it the start of a true downtrend that you need to keep an eye on? The article will illustrate a fast and simple way to de-seasonalize your data.
Let’s work through an example step by step: