What does the bounce rate in Google Analytics mean and how to configure it
The bounce rate in Google Analytics is determined by session duration and user actions on a website. The bounce rate calculation can be adjusted by changing the settings of web analytics tools.
What is the bounce rate
Let's suppose a user visits a website page. He did not perform any actions and stayed on this page for 30 seconds, and after that, he left the website. In this case, the bounce rate for this particular user in Google Analytics will be 100%.
You only have to meet one condition to result in a 100% bounce rate in Google Analytics, namely, to visit a single page on a website without visiting other pages of the same website and without performing live actions such as watching videos, downloading files, adding goods to the basket, etc.
As a result, if a user:
These conditions are considered unobjective. After all, a person can stay on one page for a long time and do what is required of him. For example, read a news article or an entry without going to other pages. In this case, a 100% bounce rate will be an illogical indicator.
On the other hand, a visitor can bypass several pages without reading the content, and eventually leave the website. A report in Google Analytics will show a 0% bounce rate which will also be unobjective.
The bounce rate data is displayed in the main section of Analytics:
You only have to meet one condition to result in a 100% bounce rate in Google Analytics, namely, to visit a single page on a website without visiting other pages of the same website and without performing live actions such as watching videos, downloading files, adding goods to the basket, etc.
As a result, if a user:
- only spent time on one page without any actions, the bounce rate of that session will be 100% regardless of the session duration;
- visited one page, added a product to the basket and left a website, the bounce rate will be 0%;
- visited one page, quickly went to another one and left a website, the bounce rate will be 0%.
These conditions are considered unobjective. After all, a person can stay on one page for a long time and do what is required of him. For example, read a news article or an entry without going to other pages. In this case, a 100% bounce rate will be an illogical indicator.
On the other hand, a visitor can bypass several pages without reading the content, and eventually leave the website. A report in Google Analytics will show a 0% bounce rate which will also be unobjective.
The bounce rate data is displayed in the main section of Analytics:
There are no bounce rate standards. For a single-page website, a bounce rate of 90% is normal, and in the news portal, this figure can reach 70% because users only visit certain pages. This data helps to conduct a comprehensive traffic analysis, increase page conversion, and improve search engine ranking.
High bounce rates of particular pages indicate user dissatisfaction with content, design, usability, and other factors. If you correct them, you can reduce bounce rates and improve the page ranking in the search results.
High bounce rates of particular pages indicate user dissatisfaction with content, design, usability, and other factors. If you correct them, you can reduce bounce rates and improve the page ranking in the search results.
How to configure correct bounce rate calculation in Google Analytics
You need to add the following fragment in the Google Analytics code to make sure the bounce rate in Google is calculated more correctly:
setTimeout("ga('send', 'event', 'read', '15_seconds')", 15000); This command sends an event that says not to consider a session longer than 15 seconds as a bounce even if no other actions have been taken. The fragment should be added in the middle of the code or before the closing script tag.
The code has been recently updated, but the previous version is still working. As a result of the changes, the old Google Analytics code will look like this:
The code has been recently updated, but the previous version is still working. As a result of the changes, the old Google Analytics code will look like this:
<script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-********-*']);
_gaq.push(['_trackPageview']);
setTimeout("_gaq.push(['_trackEvent', '15_seconds', 'read'])",15000);
(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>The new version of the code will look like this:
<script>
(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,'script','//www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-********-*', 'auto');
ga('send', 'pageview');
setTimeout("ga('send', 'event', 'read', '15_seconds')", 15000);
</script> You need to specify your personal identifier of the Analytics counter instead of UA-********-*.
Google team recommends adding this command as well. They also advise using the updated version of the Analytics counter code in 2019. The old version may become irrelevant at any time.
If after the implementation of the condition on the session duration the bounce rate remains high, pay attention to the following things:
Google team recommends adding this command as well. They also advise using the updated version of the Analytics counter code in 2019. The old version may become irrelevant at any time.
If after the implementation of the condition on the session duration the bounce rate remains high, pay attention to the following things:
1
Page design. The unsuccessful combination of shades, small print, an inconvenient arrangement of blocks can repel users. The page appearance should be attractive and easily readable.
2
Data loading speed. If a person has to wait for a long time for the text, images or other content to load, they are highly likely to close the page before the content is fully downloaded.
3
Abundant advertising and automatically switched on videos with sound. These are irritating factors for every visitor.
4
Irrelevant page content. For example, a person is looking for where to buy a closet but gets to a page with general information about closets. You need to add information in full accordance with the key phrases for this page separating informational queries from transactional ones.
5
Irrelevant traffic sources. If you advertise the page on websites with an irrelevant audience, stop doing this. This advertising is unprofitable if you do not have a goal to increase traffic at the expense of any audience.
6
No call-to-action, highlighted buttons or icons. A website visitor does not have to spend much time figuring out how to purchase a product quickly.
7
No internal linking. Once on a specific website page, give a person the opportunity to go to other sections through internal links.
8
The informational value of the first screen. The h1 page title, the first banner (if there is one), the first paragraph, and all other elements that the user sees in the first screen should be as clear and relevant to the page content as possible.
Avoid common phrases and neutral images from photo stocks which may not be clear to the target audience and will ultimately lead to closing the page. Checking the informational value of the first screen is required both on the desktop and on the mobile version of the website.
Avoid common phrases and neutral images from photo stocks which may not be clear to the target audience and will ultimately lead to closing the page. Checking the informational value of the first screen is required both on the desktop and on the mobile version of the website.
A detailed analysis of the visitors' behavior and traffic sources will help to find out the reason for the high bounce rate. The respective section of Google Analytics is called "Acquisition":
It is also worth analyzing user behavior through Hotjar and exit pages in Google Analytics. Based on this information, develop and test hypotheses to improve website usability.
It will also help if you conduct a survey for a focus group of users. This can be done both offline and via pop-ups on the website.
It will also help if you conduct a survey for a focus group of users. This can be done both offline and via pop-ups on the website.
Conclusion
The meaning of the Bounce rate can be found in the Google Analytics service. In this tool, a single user visiting a single page is considered a bounce regardless of the session duration. If you update your Google Analytics code, you can set your bounce rate to show which visitors spent more than 15 seconds on the website.
The exact bounce rate shows how interested visitors to specific pages and the website are in the information presented on it. To reduce the bounce rate, it is necessary to improve the design, simplify the presentation of content and publish only useful relevant data depending on key queries.
The bounce rate is tracked in dynamics regardless of how high it is at the beginning. With each revision made and every optimization of the traffic source, this indicator gets better and becomes lower.
The exact bounce rate shows how interested visitors to specific pages and the website are in the information presented on it. To reduce the bounce rate, it is necessary to improve the design, simplify the presentation of content and publish only useful relevant data depending on key queries.
The bounce rate is tracked in dynamics regardless of how high it is at the beginning. With each revision made and every optimization of the traffic source, this indicator gets better and becomes lower.
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