Google Analytics for Your Blog

For the past 3 weeks, I have been monitoring my blog with Google Analytics (GA). While there are certainly many useful tools in GA to help me understand and improve my blog, I have only a few basic questions for now. This is a new blog, and as such, monitoring the limited amount of traffic in highly detailed ways would probably be overkill. For those who are new to Google Analytics, or just starting a blog, my recommendation is to start simple and grow with the traffic.

Therefore, I will highlight a few basic GA metrics and reports that I find very useful to bloggers.

Profile your Blog 

Before getting lost in a sea of analytics, I think it is a good idea to ask the questions that are important to you and your blog’s success. For the purpose of my blog, I would like to explore ways to build readership--but, to do that, I first need to
understand my audience better, which brings up a few questions:

• Who is my audience, and how did they get there?
• Where did they come from?
• What did they do while they were there?

It is important to know the intent of your visitors. Are they coming to the site to learn, because they want to know more about me, because I told them to (on referral), or did they arrive by mistake? To answer these questions, we have to dig a little deeper than looking at isolated metrics. The visitor’s path (how they got there), bounce rate (how long they stayed there), and what they did once they got there can help answer our questions.

Who are they, and how did they get there?

To attempt to answer these 2 questions, I must determine things like location, gender, habits and other characteristics of my visitors—more specifically the demographics and psychographics. Demographics are things like age, gender and location. Psychographics are the “interests, occupations, roles in life, predilections and other personal characteristics” of individuals (Weintraub, 2012).

Google Analytics affords us some of this information already. Demographics information in GA includes language and location, so we can determine (regionally) where our visitors live and what language and cultural barriers may exist.

As the pie chart above shows, most of my traffic is coming from the Charleston-Huntington area. To be exact, 45.45% of my visits come from Charleston-Huntington, while 28.57% of new visits come from Charleston-Huntington. 100% of the visitor data in my report is from the United States, and the language is also “en-us.”

Since this is a new blog, I happen to know that most of my traffic is coming from my own visits to the site, so I want to eliminate my personal visits (or internal traffic) from the site data.

To do this Google Analytics Supports offers specific instructions here:

http://support.google.com/analytics/bin/answer.py?hl=en&answer=1034840

To summarize, GA allows users to eliminate data reporting for visitors with specific IP addresses ("Exclude internal traffic," 2012).

GA also provides some psychographics information, or at least room for psychographic interpretation. Determining psychographics with GA, is not an exact science, but exploring data such as “Technology” and “Mobile,” we can learn how visitors are accessing our site, and perhaps make some assumptions as to income level, technological preferences, etc.

This chart shows that most of the traffic is arriving at my blog via Google Chrome. I know that IE is a more common standard browser than any of the rest, so this data could suggest, for instance, that my visitors are web savvy users. In addition to browser information, GA allows us to determine mobile data, carrier information, screen resolution and more technological data. I know that none of the users accessing my site have done so with their mobile phones, and 100% of the visitors are using a PC, not a MAC. This information can be found in the secondary data fields of “Technology” and “Mobile” in GA’s standard reporting tool.

For more detailed demographics and psychographics data, I would suggest adding a survey tool called UserReport to your blog site. Upon viewing GA’s App Gallery, I located the UserReport software, which “enables you to combine GA data with UserReport survey data, including: Age, gender, income, education, occupation and satisfaction on 10 usability parameters (UserReport.com, 2011).”

To find out more about UserReport, please visit the following link:

http://www.userreport.com/#!prettyPhoto

Where did they come from?

GA’s “Traffic Sources” tool provides plenty of options to report on how traffic arrived at your site. My site has 45.45% direct traffic and 54.55% referral traffic from Blogger.com. This tells me that 54.55% of my traffic probably arrived because 1) my classmates are on blogger looking for my site OR 2) blogger does an excellent job of promoting my site. In this case, I will assume my classmates are visiting me. The other 45.45% of traffic is arriving “directly” by bookmark or direct entry of my URL.

The missing element here is “search engine” traffic. Currently, 0% of my traffic is coming from search results. This is a good indication that my site needs some developmental work. Perhaps my website is not being recognized (or visible) by search engines yet, or it may be that the site is too stagnant. I may just need to continue blogging to attract more positive search results and overall interest in the blog. These are things to consider when 0% (or a low percent) of traffic is from search results.

What did they do while they were there?

GA’s “Traffic Sources” resource also helps users understand the bounce rate as is relates to segments of a website audience. To explain the importance of bounce rate (BR), a high BR usually indicates that visitors are arriving by mistake or the content needs to be improved—or both. The “Traffic Sources” resource is able to identify high and low performing traffic sources, by combing bounce rate with segmented traffic data.

I particularly found the tool useful when looking at the bounce rate of direct traffic versus bounce rate of referral traffic, as shown below.

Source                    Visits  Pages / Visit   Avg. Visit Duration % New Visits Bounce Rate
blogger.com/referral     7 6.43     0:06:10             42.86% 0.00%
(direct) / (none)            6         2                  0:00:07             83.33% 33.33%

First of all, my blog is fairly new, so a count of 13 visits is to be expected (at least I expect it) at this point. I see that my “Pages per Visit” from referral traffic is an average of 6.43, which is pretty good. Again, I would imagine I personally helped boost that number, but I can control my own impact on the numbers as explained earlier. If I were judging bounce rate to determine where ads are over/underperforming, I would say a bounce rate of 33% or less is great. I would definitely place targeted PPC ads on a site with excellent bounce rates like this, but it would only be worthwhile if the traffic increased drastically.

GA’s “Visitors Flow” resource is great visual tool to illustrate how visitors interact with the site once they get there. This tool is “a graphical representation of the paths visitors took through your site, from the source, through the various pages, and where along their paths they exited your site (“About the Visitors,” 2012).”

There are many more tools, reports and functions in GA that can help us understand and optimize the experience for our visitors. For bloggers, trust and conversions are often key metrics too. Trust is often associated with direct traffic because it indicates the site has been bookmarked, or is familiar to the user (Smith, n.d.). Of course, owning a successful blog also requires others factors that have nothing at all to do with GA. Bloggers have to write content—good content—and be interactive by participating in the commentary and responding to feedback. Through effective blog management and use of the GA resources, marketers can strategically build better relationships and trust, drive traffic, and encourage new visitors.

References

(2012). "About the Visitors Flow Report." Google Analytics. Retrieved on November 26, 2012 from
       http://support.google.com/analytics/bin/answer.py?hl=en&answer=1709395

(2012). "Exclude internal traffic." Google Analytics. Retrieved on November 26, 2012 from
       http://support.google.com/analytics/bin/answer.py?hl=en&answer=1034840

Crist, M. (2012). “Web Metrics and SEO.” Retrieved on November 26, 2012 from
       http://webmetricsandseo.blogspot.com/

Smith, B. (n.d.). “Discover How to "Fix" Your Marketing with Our Free Newsletter." FixCourse.
       Retrieved on November 26, 2012 from http://fixcourse.com/blogging-succes/

UserReport.com (2011, May 31). "Get demographic data in Google Analytics with UserReport." Google
       Analytics. Retrieved on November 26, 2012 from
       http://www.google.com/analytics/apps/about?app_id=1174001

Weintraub, M. (2012, September 13). "Psychographics Deconstructed: What We Look Like to Facebook
       Marketers. SEOmoz. Retrieved on November 26, 2012 from
       http://www.seomoz.org/blog/psychographics-deconstructed-what-we-look-like-to-facebook-
       marketers