Chapter 4 of 12:
Hi! Welcome back, stranger!
I am happy to report that this week has been crazy busy and super productive with the help of the skills I’ve been learning from CXL. If there is anything that I can say that may help you in making up your mind about taking a CXL course or pursuing one of their mini-degrees, I have never taken a course that has allowed me to immediately apply what I’m learning and look like a damn Rock Star while you’re doing it! But, seriously…I’m not even kidding!
In just the four weeks that I have been taking these digital analytics courses, I have filled in a lot of the gaps that were contributing to my bouts of “Imposter Syndrome” (Yes, this really is a thing. I know, it was news to me, too. 🤯) whenever I wasn’t 100% sure what my team members were talking about. If nothing else, these courses have improved my confidence in what I’m doing and how I’m doing it. If you haven’t checked them out yet…do yourself a favor and do that!
Okay, let’s get down to what I have learned this week. I worked on these three fantastic courses this week:
- Google Analytics Audit course by Fred Pike
- Google Data Studio by Michelle Kiss
- Advanced Google Tag Manager by the one and only, Simo Ahava
I completed Google Analytics Audit and Google Data Studio courses pretty quickly because, well, they’re shorter and also I am intimately familiar with both since I use/do both in my job every day. Kind of lucky, right? The Advanced Google Tag Manager course, on the other hand, I am taking at a much slower pace because, if you’re familiar with Simo Ahava you will be able to sympathize with me here, Simo is the “Go-To” Google Tag Manager expert and thought leader. If you haven’t had the good fortune of stumbling across his blog, check it out ASAP! It’s a veritable gold mine of Google Analytics and Google Tag Manager tips, tricks, and best practices. Once you’ve had a chance to check out his blog you will understand why I’m taking this course a bit slower…it’s very technical, quite code-heavy, and well, a deep-dive into the Google Analytics library and how you can use Tag Manager to tap into its potential all while pushing the boundaries of all the stuff you can do with GTM!
What I really want to talk about in this post is some of the cooler data visualization things that you can do with Google’s data visualization platform, Data Studio. If you’re interested in getting into any type of data analyst role, Data Studio is a great place to learn and practice those skills. Data Studio is an excellent tool to use for more granular analysis of your Google Analytics data, especially when you’re wanting to deep-dive into any kind of multi-dimensional analysis. GA is configured to only allow you to dive two dimensions deep into your data, there is the option of going to a third dimension if you are familiar with the pivot table function, but it’s still pretty stiff when you’re needing more agility in your analysis. One more advanced function offered by Google in the Data Studio platform is their handy CASE function which allows you to modify existing dimensions coming in from your data source. One use-case that I found this function particularly useful was with the campaign data coming in from my company’s chatbot platform, Drift. Drift is a very cool, open-sourced chat platform that is highly customizable…but, the campaign data flowing in through the Drift to GA integration was hard to understand. Instead of sending specific campaign names with the payload, it sent the Playbook ID numbers tied to each campaign. Do you see the problem here? Unless you had memorized the Playbook ID number that was affiliated with each campaign, you would waste unnecessary time going back and forth between platforms to make sense of it all. Needless to say, it was quite the headache to work around, until…I happened across the Data Studio CASE function. Let me show you how I was able to leverage this function to make the Drift campaign data make more sense:
Voila! I was able to use the CASE function to create a sort of lookup table dimension that searched through the Playbook ID numbers and assign the actual campaign name to it. So instead of having to go back and forth between platforms, my Drift team could just look at their handy, dandy Data Studio dashboard I created them and see how their campaign efforts were performing. Pretty neat, right? Yeah, that was a pretty great day for Team Tanner.
Along with the Swiss-Army-Knife-like CASE function for customizing dimensions, Data Studio also comes with the ability to create custom metrics. For example, after reviewing the Google Data Studio CXL course, I went and created two custom form dimensions (e.g., Form Views and Form Completions) and used those two metrics to address an issue that my team and I were running into with how Google Analytics calculates conversion rates. In GA, conversion rates are calculated by dividing the number of form completions from the total sum of site sessions, which only presents one version of the truth for our form performance. We wanted to know how the actual form pages were performing with regards to form pageviews and successful form submissions. How we solved this problem was by creating a custom Form Confirmation dimension and dividing it by a custom Form View dimension which gave us the Form page conversion rate that met our objectives in an apples-to-apples Form comparison.
If you’re interested in creating something similar, here is how I created the Form Confirmation custom dimension using our form “thank you” page URLs:
I’m just realizing that both of my examples are using some form of Regular Expression, if you haven’t taken the time to check that out and learn even a couple of simple expressions it will make your job exponentially more simple! Seriously though…learning regex is one of the most valuable decisions I have ever made. It saves time, energy, and helps avoid stress headaches. Trust me, you’ll thank me later.
Stay tuned, in my next chapter I’m going to share some of the Advanced GTM wisdom learned at the feet of the GTM Whisperer himself, Simo Ahava…