Site Design for Better Search Engine
Positioning - Part III
64.68.82.208 - - [11/Jan/2004:19:34:08 -0800] "GET /robots.txt
HTTP/1.0" 404 42586 "-" "Googlebot/2.1
(+http://www.googlebot.com/bot.html)"
The next parts of the log analysis data report the status and the
file size of the requested file (underlined above for illustration
purposes). By status, we are talking about error codes. A 200 is
OK. That means the file was found and given without problems. A
404 would mean an error; file not found, as was the case with our
robots.txt file. There is no such file on our server. Check with
your host for code breakdowns. They can tell you which codes are
OK, and which ones are errors. As with the last part of the log
analysis data, you can use this information for the same purposes.
64.68.82.208 - - [11/Jan/2004:19:34:08 -0800] "GET /robots.txt
HTTP/1.0" 404 42586 "-" "Googlebot/2.1
(+http://www.googlebot.com/bot.html)"
The next part of the log analysis data is the browser type information
(underlined above for illustration purposes). This information comes
in handy when developing browser specific content. It can help you
decide if browser specific content is a direction to go, and can
help you determine which browser types to design for. In the information,
googlebot identifies as the browser. Although googlebot is a spider,
it is what requested the file, so it gets identified as the browser.
64.68.82.208 - - [11/Jan/2004:19:34:08 -0800] "GET /robots.txt
HTTP/1.0" 404 42586 "-" "Googlebot/2.1 (+http://www.googlebot.com/bot.html)"
The next part of the log analysis data is the referrer information
(underlined above for illustration purposes). The first part of
the log analysis data tells you the IP that sent the request; this
part tells the actual URL that the request was sent from. In our
log, this information is provided by googlebot itself, and is not
the true referring URL page. Google inserts this information so
we can educate ouselves about their bot. If it was a true referral
URL, then this information would reveal the most about your visitors.
You know that they came to your site through that link, where they
may not have been to every page on the IP that sent them. Reviewing
the page they came from will give you clues and insights to their
interests, and help you to tailor your site to meet those interests.
OK, so now I've got all This Log Analysis Data, but what do I
do with it Again?
Aside from the things we already mentioned, lets delve a bit deeper
into the information a linked page can tell about your visitors.
Lets us say your log analysis data tell you that a particular visitor
came in from lets say Amazon.com.
What educated assumptions can you make about your visitor? The biggest
one is that they probably shop online. That means they may have
already made a purchase with a credit card. It might also symbolize
that they are bargain or cautious shoppers. People that look for
a good deal.
However, what if they came from the Amazon.com
book section? What would that log analysis data mean? We could
say they like to read, or maybe they know someone who likes to read
and were buying them a gift. Maybe they were simply price comparing
to see if Amazon.com
might be thriftier than their local bookstore. Maybe they were an
author checking to see if their book was yet available on Amazon.com.
Maybe they are into self-help books, or do self-educating at home
with books they purchase from Amazon.com
book section. By visiting that link, what kind of pricing does
Amazon.com
book section use in that section? If you look around and compare,
where does Amazon.com
book section fall into that pricing? Are they at the high end?
Are they at the low end? On the other hand, do they fall somewhere
in between the pricing? That will give you insight to your visitor's
shopping style. Are they a bargain shopper, or isn't money a factor
to them? Some of these ideas are a bit out there, but the bottom
line thing we can infer from this link is that in someway, somehow,
they like reading or know someone who does. The question becomes
how do you turn this information into an advantage for your site?
Armed with your log analysis data and the research you have just
done, lets say your research shows that Amazon.com
book section falls at the low end of the pricing spectrum. That
tells us that your visitor is a thrifty shopper. They like finding
a good deal. What kind of affiliate programs do you know of that
offer a good deal? Can you restructure any of your product or services
offerings to cater to the thrifty shopper? In addressing their reader's
sides is your content well written and grammatically correct? Do
you have educational topics on your site that the visitor could
sink their teeth into? If your investigation revealed leisure or
fantasy reading, then do you have that kind of content on your site?
In looking at all these variables, before you make any changes,
make sure that the added content fits in with your site topic. If
you can't add topics similar to their tastes, then you can at least
add affiliates similar to their tastes.
Lets use another Amazon.com
example, but this time, let us say they came from a link from Amazon's
top selling electronics area. Let us first say that anyone coming
from an online shopping link has probably bought something online.
That implies that they might have a credit card, or at the very
least, they are comfortable with the online shopping experience.
This means that half the work has already been done with these people.
If you have built trust with your site or publication, they will
be just as open to use those credit cards or checking accounts to
make online purchases from you, or one of your affiliates. Now back
to the log analysis data at hand.
So they linked into your site from Amazon's
top selling electronics area. Last time we checked, electronics
usually tend to be high-ticket items. That would imply that money
is not really an obstacle for that visitor. It could also mean that
they enjoy the finer things in life, or that they have a high amount
of disposable income. Again, you will have to do some research to
look at Amazon's
top selling electronics area pricing strategy, and see where
they fit in with the rest of the electronic sales companies out
there. You may find that their prices are at the low end in comparison,
and that could shoot all our educated assumptions to bits. They
would no longer apply. Your visitor would be the same kind of thrifty
visitor we found in the last Amazon.com
example. Are you starting to see why we say that log analysis data
is so important?
In the log analysis data examples we used above, extra information
was chopped off the end. Those are basic examples of log analysis
data reports. Some servers squish advanced data into the reports.
That log data analysis information can include the browser type,
the screen resolution, the operating system, and a host of other
computer related information on your visitor. All of that information
comes into play when deciding how to develop your page HTML. You
can then write browser specific pages, custom monitor resolution
pages, and a whole host of other things to target and control the
way your pages are displayed on your visitor's systems. You can
even use the error information to create custom error pages to redirect
your visitor back into your site.
Back
to Table of Contents
The
Importance of Log Analysis Data (Article Continues)
Other Search Engine Positioning Articles:
Related E-Book Downloads
By James R. Sanders
January 24, 2004
If you have any suggestions to add to this article,
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About the Author
James R. Sanders is the owner of Sanders
Consultation Group Plus. He has been a webmaster and website designer since
1997. He has also been involved in self employment ventures since 1992. He is
presently a contributing author of NewbieHangout,
and has been published through WebProNews
and 4Rankings.com.
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would be website designers, self employed, or those researching information
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