Case Study - How to analyze a Web Analytics Report?

Akshay Ranganath

What to see in your Analytics Report?

Once you have for the Analytics Code onto the site, what do you start to measure? Here’s a short article on it with Google Analytics and a Blog on Ubuntu Linux as an example.

The site used for recording is our own groupMAGNET blog, http://groupmagnet.blogspot.com/.

Reports from Dashboard

Visitor Count

The very first report on the site reports on the number of visits to the web site. (See article on definition of Visit).

So, in the above screen shot, on the 16^th of October, I received 89 visitors to my website. For the range from Sep 28^th to Oct 28^th, this is the highest number. For the period of I’ve also got 213 pageviews.

The question that should come in to mind now is: Why such a sudden surge?

Content Analysis

When I see that that on October 16^th there were so many visitors, I checked the Top content report. It showed something like this:

This page shows that for the 213 page views, 128 were received from just one page. This page is having a URL ending in “3-Months after Ubuntu”. So, this is the page that has created such a huge surge in the page.

Since I know that most people landed here, I want to now know if they actually found the page useful. To verify this, I invoke the report for the specific page by clicking on the first URL shown in the sceen shot above. This results in a page of the following format:

So, this page is telling me that:

• On an average, people read this page for 3:32 minutes. This is a very good time considering that the article is really small.


• But, it also tells me that 99.21% of the users bounced. This means that after reading this article, the visitor to my site navigated to some other web site. This means:




• I am offering something that is of use to a lot of readers (the huge number of views) BUT


• My site is not offering a range of solutions to keep the users hooked on.

Hence, if I were to run huge ad campaigns, etc for some other customers, it could not be a big advantage.

The next question that comes to mind is: How did people land on my site?

How do people reach the site?

To answer this question, go back to the first page – the Dashboard and look at the following report (TrafficSources Overview):

This simple report has the details that shows the mechanism by which people are landing on my site.

So, it says that the most number of users landed on my blog via Referring Sites. A referring site is any site that has a link to this blog. (Sites like Google, etc are treated as a special case and reported in the Search Engines).

Hence, my web site is famous not because a lot of people reached through Google Search but, some particularly important source is referring to my site. Who is this site? To see this detail, click on the view report link.

Here the details shows that the top traffic sources are Ububtuhq.com and Digg.com sites.

Conclusion

From the above discussion, we see that the article “3-months after Ubuntu” has drawn a lot of viewers from the sites digg.com and ubuntuhq.com. Knowing the history of what had happened, I can now conclude that:

• Digg.com and UbuntuHq.com attract good quality viewers for topics related to Ubuntu Linux


• These sites (digg.com and ubuntuhq.com) also have ability to target users who are specifically interested in a particular topic (Ubuntu Linux)


• If I have anything to say on Ubuntu, it is probably a good idea to link the article from digg.com and ubuntuhq.com since it gives me viewers who are actually reading my material. (Coupled with the fact that I got around 10 comments, it also means that they actually read the contents and try to understand it too!)

PS: Google Analytics is a free tool. Anyone with a Gmail Id can get the necessary Javascript code for implementing Google Analytics.