Analytics for People
Practical Google Analytics and best practices for analyzing and storytelling with data
Your basic orientation about this content.
I have been implementing, using and teaching Google Analytics since before it was officially born. This document evolved out of lecture notes and presentations I do in the course of my work as an affiliate professor at the Daniels College of Business, leading the analytics practice at Two Octobers, and as an organizer of the Denver Marketing Analytics Meetup.
When I teach, I always try to impart practical information, but I also try to get to the “why” behind things. In the case of digital analytics, the obvious “why” is the seductive notion that we can gather and analyze comprehensive data about people and their behavior online. That certainly compels me. There is ridiculous power in Google Analytics, which I hope to help you unleash.
There are also cautionary tales throughout what follows. Seeing a neat table of data, with carefully named and thoroughly documented column headers is persuasive. We want to believe that metrics such as New Users and Conversion Rate are what they say they are. The truth, however, is nuanced. I encourage you, here and always, to think critically. There is a fair amount of how-to information here, but most of all this is about how to be a good analyst. That is something people can do and machines can’t.