CXL Institute Digital Analytics Minidegree Review 3: Intermediate Google Tag Manager

During this week I have advanced my knowledge in Google Tag Manager by taking Google Tag Manager Intermediate course with CXL Institute. This course provides the answers for everyone who has ever faced situations when there is a need to track something that is not easily doable with standard and the most common set of Google Tag Manager built-in tracking features. As we were approaching new restrictions forced by spreading of a new covid-19 wave, I was ready to concentrate and get deeper into Google Tag Manager measurements. And thanks to Chris Mercer that was exactly what I have gotten.

To scale up our tracking capabilities, Mercer introduces ways that we can use to implement non-YouTube video tracking and tracking of non-clickable elements on our web site (think of submission forms and automated error messages that we all/most of us have implemented on our domains). When it comes to non-YouTube videos, the instructor shows us how we can search for complete container solutions that can be imported into our Google Tag Manager and used in order to setup tracking in these occasions. While importing tracking features we are given an opportunity to choose between merging these solutions with our own settings or to overwrite our own setup (this way we lose our tags, triggers, and variables). Keep in mind that the overwrite option is a predefined, so in order to save your settings check the merge option. Aside from importing other solutions we can also export our own container and use it in other Google Tag Managers afterwards. It is very important to pinpoint that we can import any solution, not only for non-YouTube videos.

Error messages are a classical example of website event that can’t be tracked through standard events. Standard events ask for some kind of easily tracked change (such as a change of the URL). In order to track changes such as messages of missing inputs or wrong inputs, we use a Visible Element Trigger. This trigger is based on CSS selector or specific ID. Mercer shows us a way how to use a CSS selector of an unclickable element to track these changes. The procedure is very simple but effective and accurate. After we determine the element, we want to set a visible element trigger for, we open the inspect option and use the right click to copy a selector (copy -> copy selector). In the trigger settings (the trigger can be found under the user engagement section in triggers) we have a box in which we copy this selector (as mentioned, we can also go with ID, but Mercer chose this option). To finish the trigger setup, we need to choose between firing the trigger once per element, once per page, or every time an element appears on screen. Also, there is an option to choose whether to fire trigger when this unclickable element is visible on 50%, 100% or any other percent of screen visibility. One of the most interesting options here is a DOM option (we can choose between DOM and minimum on-screen duration). A DOM changes whenever new element is dynamically added to DOM or an existing element is dynamically removed from DOM.

Next, the instructor covers measurement possibilities within the enhanced e-commerce report. He explains how the enhanced e-commerce report differentiates from the standard e-commerce report, by stating that the standard report answers the question what while the enhanced report also provides the answer on how. To answer the how question, the enhanced report has to provide additional information, including information on impressions, product details views, add/remove to/from a chart, promotion impressions and promotion clicks, purchases and refunding. The easiest way to track this additional information would be through installed GTM plugin for WordPress and WooCommerce integration for WordPress. If this has been set, we can enable the option in a WordPress user panel. However, it is important to check out whether we possibly have more than one pair of these information in our data layer. We use a Google Analytics debugger to check how many times we encounter this information once the pages are loaded. If we face the information more than once, the most secure way is to go back, disable enhanced e-commerce features in our Google Analytics Settings variable, then open up a page view variable, choose the overriding settings option, and then from there enable the enhanced e-commerce features for Google Analytics Settings variable.

When it comes to custom dimensions and metrics, Mercer explains how these options are used to answer the questions Google Analytics won’t answer by default. To use custom dimensions and metrics we need to set their index numbers and scope (it can be session, user, hit, or product). Once we make our dimension or metric in Google Analytics, we go to Google Tag Manger to provide needed information (use a URL variable, with before explained query option), and use it to fire a tag.

In the final lessons, I learned about table variables, JavaScript variables, event variables, cookies, and the Google Tag Manager API. I think these lessons provide a reality check for anyone that wants to become skilled in digital analytics, as they clearly lay emphasis on importance of coding skills, mainly JavaScript and regexes. I, myself, have had experience in PostgreSQL, DAX in Microsoft PowerBI, some libraries in Python, HTML, JavaScript, and VBA in Excel, so I do not find these lessons hard to track, but someone might. However, I really appreciate the way this course on more advance topics in Google Tag Manager has been organized. It provides a comprehensive approach to problems that we as digital marketers are faced with, and it uses a lot of references that are really useful, and I encourage everyone to check them out. My next step will be a course on Measurement Matrix, also instructed by Chris Mercer. As you, who follow my posts, already know, I took Google Analytics courses first, then switched directly to Google Tag Manager, so my next station (after I complete the Google Tag Manager courses) will be courses on data visualization in Google Data Studio, BigQuery and Excel. I cannot wait!