Bounce Rate is considered as a signal of engagement and we try our best to lower our bounce rate. A higher bounce rate for us simply means that people are not liking our page.
The post will give you an overview as what bounce rate actually is and how it should be analyzed differently for different channels.
What is Bounce Rate in Google Analytics?
If you ask any random marketer what bounce rate is, their answer will be something like this, “The percentage of people who leave the website after viewing only one page.”
However, this is not true. It is a simplified version of what bounce rate actually measures.
Google Analytics registers a bounce as a single engagement hit.
For example, a user enters a landing page and leaves, that may be recorded as a bounce. But if the user enters the landing page and hit play on a video that you have set up as an interaction event, and after that, the user leaves the page, then it won’t be recorded as a bounce.
Let’s suppose you are on a website and you get hit with a pop-up right away.
A few different events are fired immediately. So when you click away from the pop-up, an Interaction event is triggered.
Because of that interaction event, even if the user exit from the website right after that, the visit will not be a bounce.
Now many marketers will treat it as an “adjusted bounce rate” which simply means that you are defining bounce rate differently than Google Analytics will do.
So you can make an event and track it as an interactive event to alter your bounce rate.
What is a Good Bounce Rate in Google Analytics?
In this competitive market, no one wants to be behind the competition event with a metric like bounce rate.
There is a post on HubSpot, that give the average bounce rates for specific types of websites –
- Content Website – 40-60%
- Lead Generation – 30-50%
- Blogs – 70-98%
- Retail Sites – 20-40%
- Service Site – 10-30%
- Landing Pages – 70-90%
Bounce Rate – The Most Misunderstood Metric of Google Analytics
Bounce Rate is a widely misunderstood metrics in Google Analytics but when placed in the right context can help you in analyzing user behavior and engagement.