Every digital marketer should prioritize learning Google Analytics. The amount of free data you can gather about user activity on your site provides incredible value.
Yet, misunderstandings of how metrics are actually calculated can quickly lead to faulty decisions. Unfortunately, many marketers go into Google Analytics not fully cognizant of the platform’s nuances.
In this article, I’ll talk about five common Google Analytics misconceptions to help improve your reporting and data decision making.
1. Google Analytics Tracks Everyone Who Visits
In addition, if a user lands on a page and quickly leaves before it fully loads, the GA code may not fire, and the user might not be tracked. Server logs and click data from ad platforms may provide a more complete picture here.
In short, Google Analytics should track most people who visit, but it won’t track 100% of visitors.
2. A User Is a Person
In Google Analytics lingo, sessions are visits and users are people, right? Not so fast.
When you visit a site, Google Analytics places a cookie in your browser identifying you as a unique user. If you return to the site from that same browser before the cookie expires, you will be tracked as the same user returning in a different session.
However, say you visit the site from Chrome the first time around and return to the site in Firefox. Since you were only cookied in Chrome, your Firefox visit would track you as a new user from Google Analytics’ perspective.
Or say you visit from desktop and then visit from your phone. Once again, GA would see those sessions as coming from two different users.
The User ID feature allows sites to assign users a unique ID that will carry across browsers and devices to more accurately associate visits with the same user. For instance, if a person logs into your site from multiple devices, you could identify those sessions as coming from the same user.
3. Average Session Duration Equals Actual Time on Site
When you’re reviewing engagement data for your site, you likely look at average session duration to get an idea of whether people are spending significant time on your site. Naturally, you may assume that the number you see here accurately measures the minutes and seconds that people spend on your site. Unfortunately, not so much.
By default, Google Analytics measures average session duration as the time from the first point of interaction with the site to the final point of interaction. Without any customization to the Google Analytics account, this final interaction is generally measured as a click to an internal page.
For instance, say that a user lands on your homepage, spends 1 minute scrolling through the content, and clicks a link to your About page. They then spend 2 minutes reading your About page before leaving the site.
How long was their actual time on your site? 3 minutes.
However, Google Analytics will show an average session duration of just 1 minute, because the final interaction tracked was the click to the About page.
4. Bounce Rate Measures Instant Exits
Like session duration, bounce rate is often misunderstood and misused as an engagement metric. A common definition I see thrown around for bounce rate is “the percentage of people who leave right away after landing on a page.”
However, this definition isn’t quite accurate. Google Analytics counts a “bounce” for any user who lands on a page without completing another interaction.
So a user could land on a longform blog post, spend 10 minutes reading the content quite thoroughly, and leave without visiting any other pages. Because they didn’t technically complete another measurable interaction, they’re still tracked as a bounce and contribute to bounce rate, lumped in with the people who spent just one second and left without reading any content.
How can you obtain better session duration and bounce rate data? Implement custom events in Google Analytics to track more interactions beyond clicking from page to page. Activities like scroll tracking and PDF downloads aren’t tracked by default but indicate a user is actively interacting with a page. Best of all, these actions are easy to track with Google Tag Manager.
5. The Source/Medium Report Shows All Conversions By Source
When you’re looking at the Goals column in the Source/Medium report, you’re seeing all conversions that came from those sources, right? Not necessarily. As anyone knows well after comparing conversion metrics between an ad platform, Google Analytics, and client CRMs, conversion numbers frequently don’t match up.
Google Analytics by default uses last-click attribution, crediting a conversion to the last non-direct click. This means that if a user came from a Google search ad but returned via Facebook before converting, the conversion would be credited to Facebook.
To get a more complete picture of conversions, first of all, implement conversion pixels directly from ad platforms to be sure to count any time a conversion can be attributed to that platform. Cross-reference vs. GA conversions to call out discrepancies in reporting.
Next, learn your way around the Multi-Channel Funnels report in Google Analytics. Here, you can see when Assisted Conversions occurred, where a channel contributed to a conversion but was not the final source.
You can also look at conversion paths to see what combinations of platforms led to conversion.
Improve Your Reporting & Analysis
Take these nuances into consideration when preparing reports or conducting analysis. A better understanding of metrics will help you communicate more accurately to clients and improve the optimizations you make in ad platforms.
What other common Google Analytics misconceptions have you come across, and how do you address them? Let us know in the comments below.