Annie Cushing of Annielytics fame had a nice post yesterday pointing out the inherent fallacy of visitor-based metrics in analytics platforms.

Annie[1] was focusing on Google Analytics specifically, but almost all of her points apply to almost any other web analytics platform as well.

If I can’t be identified as the same person while using the same browser and device, how is Google Analytics going to associate me as the same user when I actually switch devices? It can’t. So I’m only a returning visitor if I come back to your site using the same instance of the same browser on the same device. And I’m a <air quote> new visitor </air quote> every time I visit your site with a different device, browser (or browser instance), app, or kiosk.

That’s true for almost everybody and just an inherent flaw with the nature of the internet and browsers.

There is one thing - and one thing only - that I find these visitor-based metrics good for, however.


Throw out the raw numbers since they have no precise bearing on reality, but when you consider that the percentage of visitors jumping from devices to device and browser to browser should remain fairly constant[2] then looking at the trendline for those numbers can be useful.

It’s useful and valid to see growth of those visitor metrics - especially if you’re in a visitor range where device jumping is a rounding error.

This is one of those cases where you throw out the baby (the raw numbers themselves) and keep the bathwater instead (the trendline).

  1. I met Annie in person during MicroConf Vegas 2014. Fantastic person and the holder of some deep, deep Google Analytics knowledge.  ↩

  2. And for any site above a certain size, that number’s going to be a rounding error.  ↩