I see many times people looking at the above report and when they spot a big bounce rate  they panic. They start screaming the page is good for nothing as only 17% of the people stay on the website while the others are leaving.

Sorry to tell you, but no, it’s not really like that.

First, bounce rate is not calculated in reference to page views but to visits. To look at the above report and say that 83.33% of  1681 people bounced is simply wrong. Just as it is to say that 83.33% of 1427 bounced (if you relate to unique views).

So, how to interpret the above report

If you are really interested to find out how many people bounced from this page we need to find out first how many people landed on it. Bounce rate is reported only to people (actually, visit sessions) who land on a page. People that visit it by coming from another page on the same website are not counted for bounce rate (they didn’t bounce in the first place).

So, go to “Top landing pages” and check the numbers for the page you are interested in. Here is what we get for the above page:

Just 5 people bounced. Really, no need to panic.

So, before doing radical changes on your website to improve bounce rate just make sure you got it right. Bounce rate can be a deceiving metric. If you really are interested in measuring it right, try implementing the real bounce rate in Google Analytics.

Here is another article on the same topic: Why Bounces is a Better Metric than Bounce Rate.

When (re)launching a website, every department of a company focuses on 2 big objectives:

• How not to loose what we have gained so far
• How to make things better than before

Everybody is planing and working like crazy for the above objectives, then the new website gets launched and suddenly, all eyes are on you: the web analyst. After all, who else can answer those questions better than you?

It’s not a very good idea to wait till everything finishes and get the tracking going at the end… nope, not wise at all. You’d rather make sure you will be able to answer the above questions in detail and some more. Based on a project we have recently worked on, here’s our web analyst’s technical checklist for (re)launching a website:

Online behavior is not offline behavior done online. This is what Joseph Carrabis explains with a scientific rigour in his book: Reading Virtual Minds, Volume I. He takes the reader through a journey from the basics of human behavior and communication to how do users interact with the online world. Once the scientific basis is understood he takes the reader through a set of experiments and case studies on how online behavioral targeting can be used for increasing performance

What I loved the most about the book is that it comes with a scientific approach towards web analytics and behavioral targeting. On one side, Joseph has a strong background in sociology, anthropology, psychology and many other interconnected sciences. On the other side he loves the web. It was just a matter of time before putting them together (around 15 years of research, actually). The Internet is a very complex communication medium. He  really treats it as such.

The book is mind blowing. At every page you find yourself saying out loud “Ohh Common, that can’t be real!” just that at the next page everything is explained and becomes common sense. Imagine this: the behavioral targeting software he built manages to identify if a user who logs in to his account really is him or is it somebody else having access to his login credentials based only by the the way the user interacted with the website. What about managing to identify the field of interest of the visitors just by the way they browsing through a website. Mind blowing, I tell you.

Web analytics tools are not about accuracy. No matter how much you try you will never get 100% accurate data. Don’t worry about it… you don’t even need it. The power of the data stays in trends and they can be satisfied with 95% or 90% or even less accuracy.

However, one thing is 100% sure in any web analytics tool out there. When a user is being identified as a returning user, you can bet on it that that’s how it is. Don’t get me wrong here. There are returning visitors that your tool sees as new ones (they delete their cookies) but all identified as returning are definitely users that have previously visited your website.

Custom variables make advanced web analytics possible and, when done right, can offer amazing insights on the behavior of your visitors. The concept behind custom variables is quite easy: when you know with high confidence that a user is part of a certain segment of traffic, you tag that user with a label that suits your interests.

Google Analytics changed the game of web analytics by making it accessible to everyone, but can it get you reports like the conversion rate of all the visitors that were once referred by a friend through a provided form on your website? What about the number of visitors that purchased on your website after downloading one of your whitepapers? No, it can’t, not out of the box. However, using custom variables and some little implementations on your website, the above reports are piece of cake.

What makes custom variables really good? It’s the fact that you can set them up to be persistent across sessions. So if a user downloads a pdf file today and comes and convert on your website next week, Google Analytics will be able to report that he is part of the segment of users who once downloaded a pdf. You will know his behavior across different visiting sessions.