Bounce Rate and Dwell Time in Google Analytics

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How is engagement measured? The bounce rate is one of the main metrics to measure this behavior. In this post we will explain what it is and how to measure it.

One of the SEO rules is that Google values ​​the engagement of users when visiting a page, understanding that those most consulted offer more quality to the user.

As Google always wants to offer quality search results, logically the pages with the most engagement will have more points to be positioned in the first places of the SERP.

What is the Bounce Rate?

Here is Google’s description of the bounce rate:

According to Google:

Bounce Rate is the percentage of sessions on a single page, that is, sessions in which the user has left their site on the login page without interacting with it.

There are several factors that influence the bounce rate. For example, the design of the site or its difficulty of use may lead users to abandon it on the login page.

Likewise, users may also leave the site after consulting a single page if they find the information they are looking for in it and have no need or desire to visit the other pages.

So basically, if someone visits a page on your website and then leaves without interacting or visiting any other page, then that visit has rebounded.

Nowadays, most SEO experts such as “SEO Experts in Dubai” are focusing on the need to overcome the high bounce rate by the better UI/UX design and shortening the buyers experience by the shortest route to buying products to increase productivity.

These are all the Digitalmarketing techniques to overcome the bounce rate. But still if you wanna get new updates on how to overcome the bounce rate then you can follow the SEO community.

When a Bounce is Not a Bounce?

This is where things get a little more difficult, so pay attention. Consider the following scenarios, with two visitors, A and B:

Visitor A: Land on our page, stay watching our content for 20 seconds and go either to the previous site or directly close the window.

Visitor B: Arrives at our page, stays reading our content by scrolling for 5 min and without clicking any other section decides to leave.

By definition, both visitors have bounced, but taking into account each other’s time on the site, we see that while User A may not have found anything useful, User B did. Two very different scenarios.

In search engines, the metric that measures this visit duration is called the residence time, and it has an enormously positive correlation with user engagement.

Therefore, when the bounce rate is used together with the dwell time, we obtain a more reliable indicator of the level of engagement of a content on a given user.

In fact, there is significant evidence that search engines are looking at residence time as an indicator of engagement:

Although you may have put all your effort and love into creating the content of a web page, quality is in the visitor’s eye. Low page retention times may indicate that you are not capturing user interest.

So what we should be doing as webmasters, is to pay attention to the bounce rates, always complimenting them with the residence times.

If we find content that has a high bounce rate and short residence time, then we have a clear signal that we are not giving users what they expect, however a long residence time can mean that we respond positively to what the user says.

MEASURING THE REBOUND RATE AND STAY TIME IN GOOGLE ANALYTICS

The most obvious way to detect poorly performing content with these metrics is to use Google Analytics and apply a filter to all your content.

However, Google Analytics can only calculate the time spent on a page if you later navigate to another page within the website itself: the measurement can only be made between two interactions on the web.

For example, if a visitor on one of your pages stays for 8 minutes and 12 seconds before bouncing back to the search engine, Google Analytics will show a 100% bounce rate and a page time of “0:00:00” that most webmasters will interpret as a dire signal.

Here is the Google Analytics quote to demonstrate that this actually happens:

Seen in Google Analytics

When a page is the last one visited during a session, there is no way to calculate how long you have stayed on it because no other page on the site has been visited since.

Therefore, if Page A is the last page a user visits during their session, that time calculation is not taken into account for that page view.

As you can see there can be a big difference between what is actually happening and what Google Analytics tells you. This difference can end up removing content from your site that is working perfectly.

CONFIGURE GOOGLE ANALYTICS TO MEASURE THE REBOUND RATE

In order to adequately reflect bounce rates and dwell times, we need to work on Google Analytics settings.

What we can do is mark the time below which a user’s session is considered to have bounced. We think that a sufficient amount of time is 30 seconds.

If someone enters a page and leaves it within 30 seconds, it is quite possible that they have not found what they were looking for. On the other hand, if someone stays longer, at least we have got some engagement (has started reading or is watching a video).

We can adjust this time very simply by adding a line of code to our GA code, in its asynchronous version. We have to add the following code as the last _gaq.push declaration in the script:

setTimeout (‘_ gaq.push ([\’ _ trackEvent \ ‘, \’ NoBounce \ ‘, \’ Over 30 seconds \ ‘])’, 30000);

The End Result for All GA Code is as follows.

<script type = “text / javascript”>

var _gaq = _gaq || [];

_gaq.push ([‘_ setAccount’, ‘UA-XXXXXXX-1’]);

_gaq.push ([‘_ trackPageview’]);

setTimeout (‘_ gaq.push ([\’ _ trackEvent \ ‘, \’ NoBounce \ ‘, \’ Over 30 seconds \ ‘])’, 30000); // –additional line (function () {

var ga = document.createElement (‘script’); ga.type = ‘text / javascript’; ga.async = true;

ga.src = (‘https:’ == document.location.protocol? ‘https: // ssl’: ‘http: // www’) + ‘.google-analytics.com / ga.js’;

var s = document.getElementsByTagName (‘script’) [0]; s.parentNode.insertBefore (ga, s);

}) ();

</script>

This script will count 30 seconds from the page load, and if it is not closed before, it will force an event for Google Analytics. Once the event has been triggered, Analytics will not count that user as a bounce even if they don’t load any more pages on your site.

The result would be that you should see how the bounce rates of your pages go down. Here you can see a picture of when the code was added:

Now we have a much better way to identify those pages that are not working.

To find these pages, I recommend navigating to: Content -> Site content -> All pages, clicking on “Bounce Rate” to order them from highest to lowest and changing the sort type to “Weighted”.

This will give you a list of pages from highest to lowest bounce rate, showing the number of page views. With this view, you can sort pages to identify the highest bounce rates and shortest page times.

Does Google use this Analytics data for SEO positioning? Matt Cutts, one of the managers of Google, explains it to us in the following video.

Alternatives to Google Analytics

Of course, you also have alternatives to Analytics. Woopra and Clicky have more accurate ways of measuring bounce rate and time on site, through a process called “pinging”. Here you can find a post about these alternatives to Analytics.

You can also try tools specifically designed to measure user behavior on the web. We especially like Crazy Egg, which also has a very usable blog.

Summary

  • Because it is a long post, we summarize it for you in case you do not have time to read it in its entirety.
  • If someone enters and leaves your page without clicking on a second page, that’s a bounce.
  • Search engines use a metric called dwell time to determine if a bounce is “good” (for example: if the user found what they were looking for) or “bad” (if the user left the page after 3 seconds because it was super seedy).
  • Google Analytics calculates the bounce rate and time on site through page views. This means that any user that bounces will appear with 0:00:00 of time on site, regardless of how long it has been.
  • The event log can be used to manipulate the bounce rate and only show us if the user leaves before the first 30 seconds (the script is above).
  • There are good alternatives to GA for more accurate data.

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