Do you do any type of user testing to determine if your target audience enjoys your content?

Do they read the long articles till the end or do they want shorter and tighter articles?

If you never ran user testing you don’t really know your audience’s preference for content length. You are pretty much guessing that what you do is the right approach.

Don’t you wish there was a way to determine how far people are getting into the content?

Well, you can do that! With a few tweaks in Google Analytics. If you also leverage Google Tag Manager, you can set up some pretty interesting things that can be extremely helpful for understanding user engagement and happiness.

Triangulating The Data

The three analytics methods which help identify problematic content include Scroll Depth Tracking, Adjusted Bounce Rate (ABR), and then Average Time On Page. Below, you can get a feel for how the three can work together to surface potential issues.

Once you identify potential issues content-wise and dig in, you can figure out the best path forward. That might be to enhance or boost that content, you might decide it should be noindexed, or you might even remove the content (404).

Scroll Depth Tracking

In October of 2017, Google Tag Manager rolled out native scroll depth tracking.

Using scroll depth tracking, you could track how far down each page users were going. And you have control over the triggers percentage-wise. For example, you could track if users make it 10, 25, 50, 75, and then 100 percent down the page. And then you could easily see those metrics in your Google Analytics reporting.

This alone is amazing to see. You can make sure your core audience is reading each long-form article. If you see that a good percentage of users stops 25% down the page, then that wouldn’t be optimal… And if that was the case, then you could adjust your strategy and potentially break those articles up and craft shorter articles moving forward.

If you want step-by-step instructions on how to set up scroll depth tracking in Google Tag Manager, check this great post from Simo Ahava.

Here is a screenshot of the tag in Google Tag Manager when I set this up. Just remember to set Non-interaction hit to true so scrolling events don’t impact bounce rate. We’ll use Adjusted Bounce Rate (ABR) to address that instead:

Here is how the report would look like. These are the percentages that people scroll down to.

If your visitors are not engaging with your content, your report would look more like the one below:

Adjusted Bounce Rate (ABR)

Standard bounce rate is skewed. It doesn’t take time on page into account.

You set up the ABR threshold (like 30 seconds or 60 seconds, depending on the length of your content). Once the time threshold is met, Google Analytics will fire an event causing the session to NOT show up as a bounce (even if the person only visits one page).

It’s not uncommon to see Bounce Rate in Google Analytics drop off a cliff once you implement ABR. And that makes complete sense. If someone visits your article and stayed on the page for six minutes, then that shouldn’t really count as a bounce (even if they leave the page without visiting any other pages). The person was definitely engaged. Here’s what that drop looked like for a website that implemented adjusted bounce rate:

Here’s an article about how to set up Adjusted Bounce Rate (ABR) via Google Tag Manager.

Average Time On Page

In a nutshell, the way Google Analytics works for Average Time On Page, it excludes bounces (one-page visits). That’s because Google Analytics needs a page hop to calculate how long somebody remained on a page. Remember, we are setting up scroll depth tracking to be a non-interaction hit, so it won’t impact bounce rate or time metrics

Therefore, Average Time On Page will tell you how long users are staying on a piece of content when they visit another page on the site. Sure, it excludes bounces (so it’s not perfect), but it’s still smart to understand time on page for users that click through to another page on the site.

Analyze the data

Now you have set up Scroll Depth Tracking, Adjusted Bounce Rate, and Average Time On Page (a standard metric in Google Analytics). When combining all three, you can better understand if visitors are staying on a page for a certain amount of time, how far they are scrolling down the page, and then how long they are staying overall on that page.

• First, review all three metrics for each piece of content you are analyzing. If you find high adjusted bounce rate, low scroll depth, and low average time on page, then there’s clearly an issue. Dig in to find out what’s going on. Is the content old, is there a relevancy problem based on query, etc.?
• You might find content where scroll depth looks strong (people are scrolling all the way down the page), but adjusted bounce rate is high. That could mean people are quickly visiting the page, scrolling down to scan what’s there, and then leaving before your ABR time threshold is met. That could signal a big relevancy problem.
• You can use segments to isolate organic search traffic to see how users from Google organic are engaging with your content. Then you can compare that to other traffic sources if you want.
• You can also segment mobile users and view that data against desktop. There may be some interesting findings there from a mobile perspective.
• Heck, you could even create very specific segments to understand how each one is engaging with your content. For example, you could create a segment of female visitors ages 18-34 and compare that to male users. Segments in Google Analytics can be extremely powerful.

Conclusion – Using Analytics As A Proxy For User Engagement, User Happiness, and Content Quality

The best way to truly find out what your target audience thinks is conducting user studies. You can watch how they engage with your content while also receiving direct feedback about what they liked or didn’t like as they browse your site.

But you can also use analytics as a proxy for engagement and user happiness (which can help you identify content quality problems or relevancy issues).

By combining the three methods listed above, you can better understand how users are engaging with your content. You’ll know if they are staying for a certain amount of time, how far they are scrolling down each page, and then you’ll see average time on page (excluding bounces). It’s not perfect, but it’s better than guessing.

And once you collect the data, you may very well choose to refine your content strategy. And the beautiful part is that you can start collecting data today.

How To Use Scroll Depth Tracking, Adjusted Bounce Rate, and Average Time On Page As A Proxy For User Engagement and Content Quality

PS. Almost every website has a high bounce rate with a standard Google Analytics setup. But it’s very misleading. People may be interested and engaged on your site and you may not even know that.