In the second of our GA engagement metrics blog series, we take a look at Google Analytics Average Time on Page.
Sounds like the holy grail of user engagement metrics doesn’t it?!
Maybe not so….
We’ll look at why this is one of the more disputed metrics in terms of accuracy and usefulness.
How does Google measure Average Time on Page?
To understand Average Time on Page we first need to understand how Time on Page is calculated.
Time on Page = time stamp of the last interaction hit – time stamp of the first hit.
The first hit is recorded when the visitor arrives on the page (pageview hit). If a visitor arrives on your page, does not interact (i.e no last interaction hit) and then leaves your website, time on page cannot be recorded. This is commonly known as a Bounce. If this is the case, time on page is recorded as “0” and it’s important to note, these are not included within aggregated Average Time on Page results, so bounces won’t reduce the Average Time on Page data.
(If you would like to know more about Bounce Rate, refer to our previous post Google Analytics – what is a good bounce rate?
You might be wondering what use Time on Page is for a site with a high proportion single-page visits / bounces.
The good news is Time on Page can be recorded for single-page visits if an interaction hit is recorded during their visit; examples of an interaction hit include:
Social plug-in hits (e.g. Facebook “like” or Twitter “tweet”)
Event hits (visitor scrolls >50%, plays a video, completes a form): Event hits are only recorded if there is no non-interaction parameter i.e. “noninteraction=false”
Ecommerce transaction hits (clicks “buy” button)
Now we understand Time on Page we can look at Average Time on Page.
Average time on page = time on page / (pageviews – exits)
From this we can deduce that the higher the Exit Rate, the less accurate Average Time on Page will be.
Exit rate is the number of visitors exiting a particular page
Earlier in the article we explained that Google can’t track the time a visitor leaves a page. Therefore, the higher the exit rate, the more instances time on page is not recorded. It should be noted that it’s difficult to have confidence in results from a smaller sample size, say a page with very few visits.
Now we understand how Average Time on Page is calculated let’s look at the pro’s and con’s in terms of tracking visitor engagement.
no interaction = no result
If a visitor leaves your page without interacting, Time on Page cannot be recorded. This doesn’t mean they didn’t read your page, it’s just that Google has no way to track when they leave.
Without other on-page interaction events set up to record time spent, you will only get an accurate view of Average Time on Page if they navigate to another page on your website.
Therefore, pages with a high exit rate are unlikely to give you an accurate Average Time on Page result. To put it another way, when a page has a low exit Rate you can be more confident in the Average Time on Page result.
Consider setting up custom scroll depth tracking or user timing hits to ensure Google has a way of measuring the time a visitor is on your page.
Standard GA cannot distinguish tab visibility
If a visitor opens a new tab whilst on the page, the clock continues to run. If they then record an interaction hit later, after they have finished in the new tab, you are likely to get an inflated time on page recording.
If you are technically minded, consider looking into the Page Visibility API and implementing it in Google Tag Manager to resolve this.
To improve accuracy of Average Time on Page simply we’d recommend having a number of interaction possibilities for readers on your page. You’ll get a much more accurate indication of Time on Page by doing this. After all, you are looking at engaging readers so the longer you can keep your visitors interested the better!
Average Time on Page should not be used as a stand-alone metric to fully understand a visitor’s engagement with your page. Single page visits with no interaction cannot be tracked and standard GA cannot distinguish between a hidden and visible tab.
Consider using Exit Rate as another metric to improve your confidence in the result. Also consider setting up custom events and other possibilities for on page visitor interaction as both of these will give you more confidence in the result.
If you would like more help understanding Google analytics data and improving the effectiveness of your marketing, get in touch.