Tags: Google Tag Manager

Scrolling is one of the primary actions users perform on a website. Tracking this behavior allows you to better understand how visitors interact with content on the page. Although GA4 can, by default, track 90% scroll depth using enhanced measurement events, this is often not enough to properly analyze user interaction. In this article, we’ll dive deeper into the possibilities of tracking scroll activity using GTM.

If you’ve worked with Google Tag Manager, you’ve definitely come across the Page View (All Pages) trigger — for example, when setting up Google Analytics 4 or Facebook Pixel . Many people mistakenly believe that this trigger listens for the page load event, but that’s not entirely true. In fact, Page View is an event that gets pushed to the dataLayer at the moment the GTM container loads (event name: gtm.js ).

One of the main problems for marketers and web analysts is the large number of tabs users have open in their browsers. These tabs prevent visitors from focusing solely on our content. That’s why marketers come up with different “tricks” to keep users’ attention. This is an even bigger problem for analysts: with so many tabs open, you can’t be sure that the user spent the entire time — from page load to a certain moment — actually on the page.

In standard Google Analytics reports, there are three metrics that reflect user behavior: Bounce Rate, Pages/Session, and Average Session Duration. While Pages/Session is usually interpreted correctly, in my experience, many digital marketers misinterpret Bounce Rate and Average Session Duration. In this article, I’ll explain what bounce rate really is — and share a method to improve it (read: measure it more accurately).

The main reason why Google Tag Manager is installed on a website is to set up analytics systems without needing a developer's help. In this article, we’ll look at how to install three core analytics systems on your website: Google Analytics, Facebook Pixel, and Hotjar.

At the time of updating this article, there are 77 types of tags available in Google Tag Manager. Of these, 75 are various pre-installed templates, such as Google Tag, Google Analytics: GA4 Event, Google Ads Remarketing, Hotjar Tracking Code, and Google Ads Calls from Website Conversion. There are also 2 types of custom tags: Custom HTML and Custom Image .

DataLayer and the data layer. When I first started with web analytics, I couldn’t figure out whether these were the same thing or different. Every source claimed something different, and I hadn't yet learned how to read Google's documentation :) In any case, I can divide my entire work with GTM into two large periods: BEFORE I understood what the data layer is, and AFTER. Although the data layer is not the simplest thing to grasp, in this article I’ll try to present the information as clearly as possible.

Google Tag Manager is one of those tools that can make your life simpler, more efficient, and in some cases, even bring in extra profit. "Why are you still struggling with tracking codes, writing massive specs, and waiting for your developer to implement them? Just use Google Tag Manager and make your life easier!" — This is something many marketers have heard before finally adopting this tool for their business needs. Sounds familiar? You need to add a tracking code to the website, so you write a task for the developer... and then wait... and wait... and wait?

If you’ve ever analyzed Facebook traffic in Google Analytics, you’re likely familiar with the situation where you see numerous referrals from different Facebook subdomains to your website.

Among the three main ways to submit a request on a website — submitting a form, making a phone call, or writing in the chat — the first one accounts for the lion’s share and is tracked much more often than the others. Most internet marketers want to know exactly which sources bring visitors who submit forms, and that’s great. But beyond successful submissions, there are other types of interactions with forms, and tracking them helps us understand why some interested users never actually converted. Let's explore how to track the following user interactions with forms (listed from simplest to more advanced):