(Chapter 1 of 12):
Let me just start out by providing a little bit of backstory context…I have been working in Google Analytics (GA) and Google Tag Manager (GTM) almost exclusively for the last 13 months. Everything that I know has been either self-taught or intuited and while I’m a reasonably quick study, generally speaking, but, in an effort to be as self-aware as possible, I acknowledge that I have quite a few foundational holes in my understanding of many things digital analytics.
Let me explain, in my last 13 months of my digital analytics quest I have been able to accomplish some fairly advanced things in both GA and GTM (e.g., Using a URL Path variable within a Regular Expression Table variable in GTM to set up Business Unit and sub-business unit product groups within the GA content grouping feature!). For those familiar with GA and GTM, I’m sure we can agree that this is reasonably advanced stuff. BUT! I still lack the necessary confidence to “talk shop” with my dev team or other technically inclinded individuals because I still have superficial understanding of other important information, such as DOM scraping, all of the functionality and utility of the Web Developer Tools, or so many other things that a digital analyst ought to know that I don’t know — I don’t know. (Does that even make sense? 🤔)
Anyhow, in this first week of my scholarship for the CXL — Digital Analytics, mini-degree program, I am happy to say that I have been humbled in realizing even on the “Google Analytics for Beginners” and “Google Tag Manager for Beginners” level classes just how much I didn’t realize I didn’t know. I have loved jumping into the GA for Beginners course. The approach that CXL and instructor, Chris Mercer have taken to teach the basics by explaining each GA report section by framing it as answering a specific question (e.g., Audience: “Who are my visitors?”, Behavior: “What are my visitors doing?, and Acquisition: “Where are my visitors coming from?”, etc.). Here is a bit of what I have learned, just in this first week:
The Common Misunderstanding of Users in GA:
In Google Analytics language, a “User” does NOT equal a person or individual, a User is, in fact, correlated to a Client ID number that is attached to the type of device that is being used. That Client ID number is what, more or less, all GA reports are based around. As I’m sure you may have surmised and I would agree, that’s a pretty crucial piece of information to know when you are evaluating and attempting to understand the “User” data that is coming in from your website. While you do have the option to enable and track a User-ID (which is attached to a single user), the understanding that the two aren’t mutually synonymous is a solid tidbit to know before jumping into GA deep-dives. Duh, right? 😳
Debunking the Common Misunderstanding between Bounce Rate & % Exit:
Even if you’re not working in the digital world, I’m sure you’ve heard of Bounce Rate, it’s one of those buzz-words that you hear or see being tossed around by your digital marketing team that no one actually knows what it means. However, it seems to either inspire fear and anguish or elated joy depending on what numbers sit in front of that percentage sign. The funny thing is, until taking the course on GA Behavior reports, I couldn’t seem to understand and couldn’t find anyone that could explain it to me in a way that really made sense. So, when you navigate to the Site Content Report section of the Behavior Report drop-down on the left hand side of your GA View, in the All Pages report you will see the Page metrics defined as:
- Unique Pageviews
- Avg. Time on Page
- Bounce Rate
- % Exit
- Page Value
Among these metrics, Bounce Rate and % Exit are by and large the least understood, especially % Exit that little guy gets neglected by so many you would think that it’s the red-headed stepchild that everyone tells jokes about. So, Mercer shed some much needed light on these two misunderstood metrics.
First, the Bounce Rate, most people (myself included) thought that this metric was calculated by Bounces (landing on, not doing anything on page, and then immediately leaving from a page) from Pageviews or Sessions of the specific page that was being evaluated…but that’s not entirely true. You see, Bounce Rate and Entrances share a special relationship here. Entrances (another misunderstood and often overlooked metric) tells you what amount of all of the pageviews on that specific page were landing page pageviews or the first page that the user landed on when coming to your site. The Bounce Rate is showing the amount of Bounces from those Page Entrances and NOT the total sessions or pageviews respectively. The % Exit, on the other hand, is the percentage of total pageviews where the user EXITED (you can interact and create page events and still be counted as an Exit) from that page. So, in essence, we thought that Bounce Rate and Pageviews were dating exclusively, and Entrances and % Exit were another different couple. BUT! We were wrong. Although we assumed that Bounce Rate and Pageviews were a couple, and that Entrances and % Exit were their own thing, <plot twist!> it turns out Bounce Rate and Entrances were betrothed and Pageviews and % Exit were the real soulmates. I know, right…? <mind blown! 🤯>
Drama, drama, drama.
Implementing GTM — Naming Conventions:
Now this wasn’t so much of an education, but more of a pleasant validation for me. I hate (with a fiery, blazing, ferocious passion) disorganization in my GTM containers. Like…to the point where I will low-key pull a Jim Halpert and accidentally trap your stapler, iMouse, and blue-tooth keyboard in gelatin, put it on your office chair, and make you sit on it…maliciously. 🤬 The Digital Analytics sphere is an emerging and often misunderstood field, and it just feels good to be validated and feel understood. So, thank you for that, CXL and Chris Mercer. I am excited to move on and can’t wait to see what else you have to humble and educate me with!