How many times have you quoted a metric plucked from Google Analytics without really knowing what it means? Fear not, you’re not alone.

For far too long now, marketers have had misconceptions over how to define one particular metric – bounce rate, either confusing it for exit rate or adding non-existent criteria. So, we’ve put together a quick-fire guide to help you become a bounce rate aficionado.

## How is the bounce rate calculated in Google Analytics?

The Google Analytics help guide is a good first stop when trying to get to the bottom of the topic. And with it, you only need to remember two key things:

1. A bounce in Google Analytics is a single-page session on a website

2. The bounce rate for a page is based only on sessions that start with that page

## What does this mean in practice?

Here’s an example with three sessions:

Imagine there have been three user sessions on your website. During these sessions, the following pages were viewed in this order:

• Session one: Page A > Page B > Page C > exit
• Session two: Page B> Page A > Page C> exit
• Session three: Page A> exit

Page A bounce rate = 50%
Page B bounce rate =0%
Page C bounce rate = 0%

Why? You might tend to think that Page A’s bounce rate is 33% because the page was viewed three times and the user only exited the website after viewing page A. It’s a typical misconception, but that logic is actually the definition of “exit rate”.

Similarly, you might be tempted to think that Page C’s bounce rate is 100%, as all the sessions that have included Page C as part of their journey have been immediately followed by an exit. However, only pages that start a session are included in these calculations.

Here’s an example with five sessions:

• Page B > Page A > Page C> exit
• Page B > exit
• Page A > Page C> Page B > exit
• Page C > exit
• Page B > Page C > Page A > exit

Page C’s bounce rate is 100%. It has been visited four times, however, only one session started with it. It is, therefore, the only one counted by Google Analytics in its bounce rate calculations.

## What is an exit in Google Analytics?

Simply put, an exit is when a user exits the website in one way or another.

This means that if one of the goals of your website is to get users to click through to a third-party retailer after visiting a product page, users will need to exit the website in order to be counted as a conversion.

In this particular case, you could theoretically have pages with both a 100% bounce rate and a 100% conversion rate at the same time. But is lowering the number of single-page sessions on your website really your objective?

If not, you might want to consider a different KPI for your business. For SEO marketers, it is often the “go-to” KPI when reporting on performance, but others – such as exit rate – might be a better fit depending on your website’s objectives.

## How should we use bounce rate and exit rate for efficient reporting?

### 1. Bounce rate at a website level

At a website level – the figure typically found on the Google Analytics dashboard – bounce rate only means the percentage of single-page sessions compared to overall sessions.

Due to its default settings, Google Analytics can be misleading as it will indicate a decreasing one with a green arrow, suggesting it is “good”, while any upturn is marked in red and perceived as “bad”. However, having a higher bounce rate can be a good thing – perhaps the user only needed to visit one page in order to find the information they needed. This entirely depends on the type of website you are reporting on and the content it serves (ecommerce, blogs, informational, and the others).

Changes in bounce rate at the website level should not be used to evaluate website performance, but rather to notify a change that requires further investigation.

### 2. Bounce rate at the page level

If it increases for a particular page, it is important to evaluate the type of page to understand if the change is positive or negative:

#### A non-exhaustive list of examples

• Homepage: an increase in bounce rate is generally negative and means less users are willing to visit a website beyond its home page.
• Content/article: an increase in bounce rate could mean that users have found the information they need. In this case, bounce rate alone cannot be used to determine a positive or negative change.
• Product page: an increase in bounce rate on pages with ecommerce functionalities needs to be analyzed in conjunction with recent website template changes to ensure the user experience is not negatively impacting shopping experience.

### 3. Exit rate at the website level

At a website level, the exit rate does not provide very meaningful data because users will always have to exit a website from one of its pages at some point.

Google Analytics still provides this type of data under the behavior tab, but it is not recommended to use this information to report web performance.

Exit rate at the website level cannot be anything other than 100%. However, be aware that Google Analytics takes an average of the exit rates for all pages of the website to come up with a “website average”.

### 4. Exit rate at the page level (or set of pages)

This is where the exit rate really shines. If you have an ideal user journey for your website, the exit rate can help you identify changes in user behavior. From there, you can tweak web page templates to bring users from one point to the other – using multiple pages and monitoring where users exit – and therefore finish their journey.

Now that you’ve mastered the difference between bounce rate and exit rate and how to use them effectively in your reporting, it’s time to put your knowledge into practice. Log into Google Analytics and start to delve into what these stats really mean for the website.

The post Want to reduce your bounce rate, but what does that actually mean? appeared first on Search Engine Watch.