Google records 1.2 trillion searches per year worldwide. Nearly processing 40,000 searches every second. Most businesses rely on Google Analytics (GA), a freemium web analytics service to measure traffic and effectiveness of their marketing efforts. GA helps marketers to uncover insights from data which can then be turned into marketing deliverables. However, most marketers now consider the Google Analytics as a black box when it comes to measuring user engagement.
Measuring User Engagement Using Time on Page
Traditionally marketers have measured user engagement using metrics like Time On Page. This metric measures the amount of time user spends on your website. With default implementation of Google Analytics (GA), this metric might not be a reliable means to measure user engagement.
Google Analytics measures time on page by studying the difference between the time of the first and the time of the last hit. Please view the below example to see how this works.
In the above example, the difference between the first hit (10:00 am) and the last hit (10.10 am) is ten minutes. Therefore Time on Page will be considered as ten minutes.
Why is Time on Page, not a reliable Metric?
In the above example, 10:10 is not the time when the user left the website. The user could have spent an additional five minutes on page 3, and Google Analytics has no idea because no further hits were fired.
For instance, let’s say you sell widgets and someone clicks through your widgets products page. They look at images, scroll down and read reviews, click a tab to read specifications, maybe even click to add the product to a dynamic cart that doesn’t reload the page. They finally leave the page but are still considering to purchase without going to another page. A default GA implementation would register the view of the page that’s it. No time on page would be recorded because its only determined by the time on next page view in Google Analytics. For marketers, this means that, by default, Google Analytics’ Time on Page and Session Duration metrics are lower than the actual value of how long someone spent on a page or site.
In case of content sites, this means even if the users read, scroll thousands of pixels and get to the end of the article but to choose to close the tab without visiting an additional page no time on page would be recorded.
What if we used Event Tracking or Scroll Tracking?
So how do you fix this problem? You can use a timer trigger on Google Tag Manager, that fires at 30 seconds, or 1 minute after the page loads in the browser but well it won’t fix the issue. As timer triggers fire based on the time the page gets loaded which doesn’t mean the user is engaged. Also if the user has multiple tabs opened up in the browser, then your time on page will keep going up, but it wouldn’t mean that the user is engaged.
To measure whether a user is engaged we could measure the scroll of the content. That’d be a good measure of user engagement right? But what if the user scrolled really fast, took just 5 seconds to skim through content that would have taken them 5 minutes to read. Would you consider the user to be an engaged user? If someone actively was engaged on the tab, on the page, with mouse movement, and scroll movement, for over 4 minutes, and reached the end of the page. That person you could surmise read the content. Then your metric isn’t ‘time on page’ but rather understanding whether the user ‘actually consumed the content’.
This applies to product pages as well. You could have an awesome time on page for a product, but if they’re not actively engaged with the page, scrolling, clicking on alternate images, on review tabs, etc. Just because the browser is open doesn’t mean the user is engaged.
It’s not easy to measure whether a user has actually engaged with your content, but then it gets you an audience segment. For instance, you could track all users who actively engaged with your widget page for at least 1 minute through a variety of actions (clicks, scrolls, etc). You can use this information to remarket ads to this new audience segment instead of targeting the entire database. This would certainly improve the Return of Advertising Spends (ROAS) and Cost Per Click (CPA).
Possible Solutions to Measure User Engagement
To measure whether the user actually consumed the content, you have combine data from different sources. Combing data from disparate sources including heatmaps, sessions recordings and event triggers will allow us to improve page flows and measure engagement more holistically.
In the end, the question really is what are we trying to do, how are we trying to help our customers. I seriously doubt most companies have a real metric of “time on page” as something that they’re aiming for as an end objective. They want to sell widgets, and assuming that a default GA metric is a solid measure of funnel activity to that end is flawed. What we need to be doing is measuring actual human (not browser) engagement, and how their actions correspond to conversions. How many people viewed the CTA on the content page? How many people clicked it? Of the people who clicked it, how long did it take them to click on it? How many people never scrolled the page at all and were really a “soft bounce” no matter how long they sat there? There are lots of ways to measure and understand the path of your customers, and time works into it, but just caring about a generic “time on page” metric? It’s not really helpful.