Now I've come to the hardest task in
Web analytics: the actual analyzing part.
I'm most interested in finding out who
is visiting my site in an attempt to discover how to bring them back
again to consume my wonderful content. My main driver of traffic to
this blog was a post on June 14 that I wrote on Facebook asking
family and friends to check out my blog.
Since that time, I've had eight unique
visitors who have made 13 visits with 43 pageviews. You can see from
the chart below that they mostly occurred in one spike. The day I
posted the blog link on Facebook is the day I got the most traffic of
seven visits. I was curious as to who these folks were so I could
reward these most loyal with high-priced Christmas presents.
Location
The most visits to the blog came from
Morgantown, followed by Broward County, Fla., where one of my friends
works. You might find the Moscow entry interesting. I know it to be
from my one and only friend in Moscow, Idaho, who has clearly visited
the site twice. In a conversation with him (market research, if you
will), I discovered that he tried to comment on the site but was
unsuccessful. I view this as customer feedback on the technical
details of my site.
Then I got one visit from Lake Worth,
Fla., where my brother attends college and one from West Palm Beach,
Fla., where I grew up. This last entry should clearly be labeled
“Mom.” Luckily I always get her something nice for Mother's Day.
I would add a caveat that I don't think
location is always an important metric to check. But since the blog
has had so few visitors and the locations vary so much, the metric
works in this case. For my company's news site, the location data
typically shows that most visits come from Morgantown. It's great
that the city's population is so engaged with the site, but this
isn't great for attracting new students from other locales. It's
similar to the new versus returning visitors debacle. You want growth
in each, but you can't merely attract returning visitors (Kaushik,
2010).
Use Dimensions
But I'd clearly want to know who the
people in Morgantown are. I know a lot of folks in Morgantown, and I
really would like to know who is deserving of better Christmas gifts.
So I went to Referral Traffic under the
Traffic Sources tab. I did get most of my referrals from Facebook,
but I also got three referrals from blogger.com and all of those
visits were from Morgantown. I'm positing that these visits could be
from friends who have blogs or a classmate who lives in Morgantown. I
found out that these visits were from Morgantown by selecting City as
a secondary dimension.
For non-ecommerce sites
Ever since I read Avinash Kaushik's
suggestions on key metrics for sites that do not have an e-commerce
component, I've been eager to try them (Kaushik, 2010).
Frequency and recency are both
discussed in Kaushik's book, yet they must have displayed differently
when he wrote it a couple of years ago (Kaushik, 2010). This spring,
he wrote a blog post on the usefulness of analyzing the now combined
frequency and recency reports.
Count of Visits
Kaushik likens visits to relationships,
calling single visits one-night stands (Kaushik, 2012). From the
Count of Visits report below it appears that I had 13 visits with 43
pageviews. I ran the report again with an advanced segment of
returning visitors and had five visits from returning visitors. One
of these included 16 pageviews. These are the visits I'd like to keep
an eye on.
Days Since Last Visit
The Frequency and Recency tab also has
a Days Since Last Visit segment to measure recency. There's nine
visits today and two visits the day before. When you compare it with
the following Returning Visitors segment, you'll see that a lot of
these visitors have been recent but have been one timers. This isn't
what I'm going for, but I know that I need to let my visitors know
about my new posts to get them to keep coming back.
Visit Duration
In the Visit Duration tab, Google
Analytics is showing me that most of my visits are lasting fewer than
11 seconds. I have had two visits that have lasted more than three
minutes. To find out how to replicate the success I've had with these
visitors, I should look deeper into where they came from and where
they looked for so many minutes. I'll go into how to do this in a
later post. I will add a caveat that Kaushik mentioned (2010).
Because this is a blog, it will probably get a lot of one page
visits. Analytics systems have no way to measure the length of visits
that only last one page, so sadly no matter how long they are, they
don't count for visit duration.
Page Depth
Most site visits included two pages.
Only three visits were to more than two pages going up until 16
pages. I'm not sure that this statistic is going to change much
because it is a blog, but for other sites, you'd want that number to
be a lot higher (Kaushik, 2010).
Bounce rates
I was surprised to
see that my site has a zero-percent bounce rate. Checking in with my
Kaushik text, I remember that blogging sites typically have high
bounce rates because visitors usually go to a blog site and then
leave after they've read an update thereby showing many visits
consisting of one page only in the analytics report (Kaushik, 2010).
Maybe my visitors are just more thorough because they're friends and
relatives.
What should I do differently?
The question you
have to ask yourself is whether you should change anything based on
your newfound analytics knowledge.
Since I have a
blog, I want to increase readers, but I also want highly engaged
readers; those who keep coming back, offer comments and get something
out of my posts.
My blog is new,
but I can still work on some preliminary ideas. I want my new
visitors to return, so I have to make it easy for them. I'll
encourage them to subscribe to my blog via an RSS feed. I'll also
have to create content regularly enough to keep their interest. And
I'll have to work on making my blog more interesting.
To that end, I've
included screenshots of the Google Analytics reports I've referenced.
Finding ways to use multimedia clips where necessary will also work.
I'll work to keep a conversational style, and I'll work on directing
my blog toward people who would find it interesting. My Facebook
friends are mostly not marketing folks. But my classmates and
workmates are mostly marketers. So I can try to link to as many of
their blogs as possible.
An additional
metric to think about is keywords.
I didn't run any
reports on keywords because no one came to my blog by searching for
it. But I could change that by making sure I'm including relevant
words in my posts so that if anyone were searching for information on
my blog, they'd be likely to find it.
On the Traffic
Sources lesson in the Google Analytics IQ lessons, there's a helpful
segment on correlating keyword searches with landing pages.
(Google Analytics,
2011)
References
Kaushik, A.
(January 30, 2012). Google Analytics tutorial: 8 valuable tips to
hustle with data! Retrieved from:
http://www.kaushik.net/avinash/google-analytics-tutorial-8-valuable-tips-to-hustle-with-data/#rfm
Kaushik, A.
(2010). Web Analytics 2.0: The art of online accountability &
science of customer centricity. Indianapolis, Indiana: Wiley
Publishing, Inc.
Google Analytics.
(2011). Traffic sources. Retrieved from:
http://www.google.com/analytics/iq.html








