A Rejection Rate shows us the percentage of users who visited a single page and then "abandoned" it. We'll see throughout this article that a high bounce rate can be extremely valuable for a website.
Assuming you are using the Google Analytics, in the Behavior tab and in Overview, we can see the percentage of the site's Bounce Rate.
- Arrives at your page;
- Like your product;
- Look at the phone number;
- Make the connection and close the page;
You have a new potential customer, a new sale, but the GA (Google Analytics) script has no idea how relevant the page is to the user, much less how relevant the user is to the page. But as mentioned before, Google follows scripts, and what do our lines of code say? "If the user doesn't interact with other pages and closes this one, we count it as a bounce." And there goes the bounce rate being unduly increased.
Another fact that we can analyze is the following:
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You send a E-mail marketing;
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The user clicks and lands on your page;
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You like the product and want to make the purchase;
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At the time of purchase, the user is thrown off the site to complete the payment (with PayPal or PagSeguro, for example). In this case, we have a relevant, satisfied, and happy user, but BINGO! Bounce Rate wins again.
The Solution to Lowering Bounce Rate: Adjusted Tracking
There are countless ways to optimize our GA Script to obtain different numbers and data on the dashboard, including more robust ones than the example used below (I will present them in new articles on the subject), but since the intention of this content is to show in a simple and quick way how to improve the numbers, this metric serves perfectly!
Google gives us the freedom to add different functions to change how our GA Script works according to our needs and data collection goals. As presented by Google Analytics Blog, you can enter a time "x" to determine whether or not the user is engaged with the landing page. Therefore, validations of future clicks and navigation within the site are discarded, and the minimum time the user must remain on the page to avoid being considered a "bounce" becomes valid.
In the code, few changes should be made, only one line insertion is necessary:
Where UA-XXXXXXXX-1 is your Tracking ID and in the bold line, the value in seconds that is actually considered a valid time for an engaged user must be changed, for example, it could be changed to 15 seconds:
setTimeout(“_gaq.push(['_trackEvent', '15_seconds', 'read'])”,15000);
If you're using the standard version of GA, your Bounce Rate simply refers to users who didn't move forward on your page. This is just a metric; it doesn't mean good or bad news. The next time you analyze your Bounce Rate, think about your goal with this number and the way the user interacts with the website and the script's objective.
Want to discuss Bounce Rate? Tell us what you think of this metric and how you implement it in your business!
