Have you seen the benefits of tracking adjusted bounce rate in Google analytics? The bounce rate is an important statistical parameter for quality of site traffic as it tracks how frequently your site visitors exited or ‘bounced’ from your landing page after viewing a single page only. Google search algorithms give lot of importance to the bounce rate of your site to determine search engine rankings.
Google analytics defines bounce rate as the percentage of single-page visits (i.e. visits in which the person left your site from the entrance page). If a site visitor lands on your site, reads the content, and then clicks the link to go to out of your site, it would lead to a high bounce rate. It would signify in some way that the visitor did not want to further browse your site content, may be due to slow loading content, poor content, difficult navigation or any other reason. But the main fact is that your site visitors left and ‘bounced’.
Adjusted Bounce Rate
Google analytics recently produced a new way to track your bounce rate called adjusted bounce rate. This is different from the standard bounce rate because sometimes landing pages DO get the attention they need and the visitors do NOT bounce off the page because he did not enjoy the content.
What if he performed the call of action which the landing page desired. What if he read your 1000 word article, found the solution for which he came via Google search, and closed your site tab. So this adjusted bounce rate adds a new factor taking to amount the time spent on the web page and integrates it with the bounce rate.
Google analytics code change
They suggest you modify your Google analytics code and add another line like this
setTimeout("_gaq.push(['_trackEvent', '15_seconds', 'read'])",15000);
So the code at the beginning would look something like this now
var _gaq = _gaq || ; _gaq.push(['_setAccount', 'UA-XXXXXXX-1']); _gaq.push(['_trackPageview']); setTimeout("_gaq.push(['_trackEvent', '15_seconds', 'read'])",15000);
This executes an event when a user has spent over a certain amount of time on the webpage, for example 15 seconds in this case. Google advises that this code change should be done on websites with landing pages where Webmasters want a more in-depth analysis into user behaviour and time spent on the website.
We implemented the adjusted bounce rate code to our Google analytics code a few days back and see the result below.
You will observe that the bounce rate which was nearly 80%, has now come down to around 14%. The average visit duration has increase from around 50 seconds to nearly 1 min 10 seconds.
So I would interpret it like this – 80% bounce rate means 80% site visitors browsed only the single entry page or Landing page and left the site or closed the browser. However, adjusted bounce rate reveals only 14% site visitors spent less than 15 seconds time on the entry/landing page and then left or bounced off the page. These people were more likely to not have found the desired content and ‘bounced’ and this seems a more practical use of the bounce rate. I’m not sure why the average visit duration would increase with the code. Surely this metric has helped us to get a better insight into the bounce rate of our website.
If Google starts tracking the adjusted bounce rate into the algorithms, it would be interesting to observe the search engine rank changes. What is your adjusted bounce rate?
Update: Here is the updated code to track ABR in Universal Analytics