“How come the %Exit metric doesn’t say 100%? Everyone has to leave a website at some point, right?”
Measuring how visitors interact with your website – and how they consume your website – is the critical way in which you can refine and improve your website to provide an increased level of visitor satisfaction, and a higher profit margin.
Entrances, bounces, and exits are three foundational, bedrock metrics that Google Analytics uses in many different ways to help you measure your website’s effectiveness. As it turns out, there seems to be slight to moderate confusion about what these metrics represent, and what metrics like bounce rate and %exit really mean.
Let’s start by defining the aforementioned three foundational metrics:
Entrances – This is the number of entries by visitors into the pages of your website.
Bounces – This is the number of single-page visits by visitors of your website.
Exits – This is the number of exits from your website.
Pretty clear so far, right? Good. Now, it starts to get slightly trickier. How about we define another metric:
Bounce Rate – This is the percentage of single-page visits to your website. Bounce Rate is calculated by dividing bounces into entrances.
So, when you have a 60% bounce rate, 60% of your entrances left your website on the same page they entered from. In other words, they did not view another page. Also, when you have a 60% bounce rate, Avinash Kaushik’s head explodes. 🙂
Still with me? Great! Now let’s define the last of our metrics:
%Exit – This is the percentage of site exits from your website. %Exit is calculated by dividing exits into page views.
A-ha! You probably already knew or had an inclination toward what the first part of the definition would say, but then reading the second part, you start to see why the %Exit metric isn’t ever equal to 100%.
Now let’s take the final step.
Does everyone have to enter your website to view it? Yes. Does everyone have to leave your site at some point? Yes, they do. So, while the %Exit metric isn’t going to be 100%, the number of total exits should equal the number of total entrances.
A few images will help you understand everything you’ve been reading so far. I created a custom report in the new Google Analytics platform showing entrances, exits, page views, %exit, entrances / page views, bounces and bounce rate metrics. I also have the page as the dimension for my custom report. This first image shows the scorecard, which tallies up the totals for all metrics for the dimension that I have chosen:
As I expected, the number of total exits equals the number of total entrances (everyone has to come in to some page and everyone has to leave at some point). But the %Exit metric reads 58.92%, not 100% as you would initially think. So, I threw in the page views metric to give you some clarity as to how Google Analytics is calculating %Exit. 13,467 exits divided into 22,857 page views, all multiplied by 100% will give you 58.918%, which is rounded up to 58.92%.
However, viewing the very first line item of my custom report shows that the number exits does not equal the number of entrances for any given page, because not everyone leaves your website on the same page that they entered it from:
Here, the %Exit metric makes a little bit more sense, as it is not tallying up page views for all viewed pages on the site – only the /index.php page. 43.91% of all page views on the /index.php page resulted in an exit from the website from this particular page.
I hope that you were able to obtain some clarification and some deeper understanding of how some of the common metrics that you see in Google Analytics are tabulated and used by Google. Remember to always know what data you’re looking at – that is, get to be familiar with the way metrics are computed in Google Analytics (or, your web analytics platform of choice), as it will help you glean those insights that we all strive for!
When talking about Google Analytics or Web Analytics in general, some metrics and reports get seemingly all the attention (and rightfully so). Metrics like Bounce Rate, while loved by Web Analysts on all corners of the globe, are just too popular. In fact, Bounce Rate is now trendy! Do you think it’s become a buzzword as well?
Anyway, while Bounce Rate, Revenue, Goal Conversions, and Transactions are as popular as your local high-school’s starting quarterback / class president / homecoming king, there are other metrics to look at in Google Analytics, you know! These next five metrics are probably some that you’ve seen before in reports, and probably available in SiteCatalyst, WebTrends, ClickTracks, and other Web Analytics programs, although they could be known by another name in those programs.
1. $Index – This metric basically tells you what the average value of each page is on your website. It takes the amount of either Ecommerce Revenue or Goal Value that each page was responsible for, and divides it by the number of Pageviews for each page to give you a financial value in your currency of choice. You can find it by going to the Top Content report in the Content section, all the way to the far right of the report table. Log-in to GA and bring this report up in your profile, and check out what the $Index is looking like for each page. The values may be as small as a couple of dollars, to as high as a few hundred dollars per page. The Goal here is to find that page or two that has a higher $Index than most of the other pages, that also has a good amount of Pageviews. It could benefit you greatly to further optimize that page, or, to create some special offers or promotions directly on that page.
2. % Search Exits – If you have an internal search function on your website (and if you don’t, why not?), this metric calculates the percentage of people who left your website altogether, immediately after they performed a search. These people did not go any deeper into your website, or did not refine their search at all – they simply left. Think of % Search Exits as the “Bounce Rate” of your search function. Now, there is the possibility that they found exactly what they were looking for and they are going to come back later. However, if a lot of people are doing this, chances are your search function isn’t working properly, or serving up relevant results. Our loyal readers of this very blog know that that is a pet peeve of mine.
3. Per Visit Goal Value – Another interesting economics-oriented metric, found toward the right-hand side of the main report table, underneath the Goal Conversion tab. Use this type of micro-analysis to evaluate how valuable each and every one of your website’s visits are (so basically this is $Index for your Visits, instead of for the pages on your site). And, much like $Index, this number can either be very small or very large, depending on your Goal Values and how valuable each visit is to your website.
4. Revenue Per Click – Are you noticing a trend here? If you’re advertising with Google AdWords and if both your AdWords and your Google Analytics accounts are properly synched up, this very small number can tell you exactly what the name of the metric reads – the revenue that each click on your ads generated for you. This will allow you to say “Hey, Ad “C” or “Keyword X” is delivery $0.87 a click!” This can definitely place your click management strategy under a whole new light
5. Abandonment Rate – This metric is available via the Goal Abandoned Funnels report within the Goals section of your Google Analytics profile. Having the ability to view this metric should not be an issue – because every profile SHOULD have Goals and Goal Funnels. This statistic is telling you the percentage of people that are leaving your Goal Funnel at some step along the way. Chances are that they are leaving your Goal Funnel, and not coming back to complete and match your Goal. If this number is very large, you need to evaluate the way people can get to your Goals (every page along the way). Even if this number isn’t very large, you should stay on top of the path that your visitors take to reach your Goals. It’s actually very surprising to me that this metric, and even this train of thought, is very under-utilized in Web Analytics, so I feel compelled to add it to this list.
Now log-in to your profiles and check these out for yourself!