I'm really enjoying the power of Google Analytics - I can use it to get pretty detailed information on Webmetricsguru.com traffic and conversions (IE: clicking on an AdSense ad which is defined as Goal 1 here) and I'm going to talk about that for the next couple of posts - as it's been on my mind to do it - and it's Christmas.
OK, what did I learn……For traffic that came from the United States I seemed to get the most keyword traffic when I wrote about the TMobile SideKick III (got a lot of traffic on the Sidekick 4 - which is not even out yet) and Ashlee Simpson's Nose Job - (it's mostly Long Tail Traffic - I write about what I'm interested in and tie in Web Analytics as much as I can).
Filter: Google Analytics - All Reports / Visitor Segment Performance / Geo Location / United States (2006 year to date data) / Cross Segment Performance / Keyword.
|
Keyword
|
Visits | P/Visit |
G1/Visit
|
|
(no data)
|
27290
|
1.54
|
2.24%
|
|
sidekick 4
|
1312
|
1.11
|
4.04%
|
|
ashlee+simpson+nose
|
1012
|
1.06
|
0.69%
|
|
clay+aiken
|
421
|
1.55
|
4.28%
|
|
ashlee+simpson+nose+job
|
291
|
1.08
|
0.69%
|
|
ashley+simpson+nose
|
248
|
1.08
|
0.40%
|
|
ashlee simpson nose
|
246
|
1.04
|
0.41%
|
|
ashlee+simpson+new+nose
|
234
|
1.11
|
1.71%
|
|
chacha.com
|
212
|
1.43
|
3.30%
|
|
ashlee+simpson's+new+nose
|
198
|
1.06
|
0.00%
|
|
robert.downey iron.man
|
182
|
1.11
|
1.65%
|
|
ashlee+simpson's+nose
|
162
|
1.03
|
0.62%
|
|
riding nerdy
|
155
|
1.25
|
1.94%
|
|
wierd al white and nerdy
|
152
|
1.33
|
2.63%
|
|
horny manatee
|
151
|
1.09
|
0.00%
|
|
clay aiken
|
129
|
1.66
|
3.10%
|
|
white and nerdy
|
125
|
1.33
|
0.00%
|
|
lonelygirl15 fake
|
116
|
1.53
|
2.59%
|
|
American+Idol
|
110
|
1.48
|
0.00%
|
|
ashlee+simpsons+new+nose
|
110
|
1.06
|
1.82%
|
|
ashley+simpson+nose+job
|
97
|
1.06
|
0.00%
|
|
Sidekick 4
|
95
|
1.07
|
3.16%
|
|
ashley simpson nose
|
93
|
1.08
|
0.00%
|
|
horneymanatee
|
92
|
1.36
|
0.00%
|
|
ashley+simpson+new+nose
|
87
|
1.05
|
0.00%
|
|
fake news generator
|
84
|
1.56
|
4.76%
|
I got the most Goal 1 conversions on SideKick 3/4, Weird Al, Clay Aiken, Chacha.com and the Fake News Generator while keyword traffic (based on what I posted on) that converted the least was on popular stories like the Horny Manatee (for which there might not have been any AdWords advertisers anyway) and American Idol.
I think it's quite possible to segment keyword traffic and the results based on both location and by url (blog post in this case).
Suffice it to say that I'm happy Google Analytics matches up goals with most of the reports. I'll cover how to locate the best performing blog posts in my next post.
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