There is no doubt that Google Analytics is one of the most important tools you could use to understand your users' behavior and measure the performance of your site. There's a reason it's used by millions[1] across the world.
But despite being such an essential part of the decision-making process for many businesses and blogs, I often find sites (of all sizes) that do little or no data filtering after installing the tracking code, which is a huge mistake.
Think of a Google Analytics property without filtered data as one of those styrofoam cakes with edible parts. It may seem genuine from the top, and it may even feel right when you cut a slice, but as you go deeper and deeper you find that much of it is artificial.
If you're one of those that haven’t properly configured their Google Analytics and you only pay attention to the summary reports, you probably won't notice that there's all sorts of bogus information mixed in with your real user data.
And as a consequence, you won't realize that your efforts are being wasted on analyzing data that doesn't represent the actual performance of your site.
To make sure you're getting only the real ingredients and prevent you from eating that slice of styrofoam, I'll show you how to use the tools that GA provides to eliminate all the artificial excess that inflates your reports and corrupts your data.
Common Google Analytics threats
As most of the people I've worked with know, I’ve always been obsessed with the accuracy of data, mainly because as a marketer/analyst there's nothing worse than realizing that you’ve made a wrong decision because your data wasn’t accurate. That’s why I’m continually exploring new ways of improving it.
As a result