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Two
Limitations of Website Traffic Analysis Tools: Capturing Traffic
Data for Dynamic Content and Click-stream Analysis
by Hurol
Inan
The
technical complexity of websites have gone a long way since the
early brochure-ware websites. These websites were developed
mainly by HTML and collecting data about the traffic via log
files was an easy task.
These
days, however, many websites provide dynamic content, which is
stored in databases, and are often integrated with other
corporate applications and external service providers for
transaction processing and content publishing.
This
brings about serious limitations to the solutions available in
the marketplace. With this article, I would like explore two of
these that are not supported well with commercially available
solutions:
Capturing
Traffic Data for Dynamic Content
Log
file based analysis fails to capture the exact content the user
is looking at, if the content is stored in a database or sourced
from an external source. Log files only record the page the user
is looking at but do not record the unique identifier of the
content displayed.
A
similar situation arise when your web site publish dynamic
content directly from an external source.
With
log file based analysis, you would know that a user is looking
at an external content but you won't be able to identify what
exactly they are looking.
This
situation worsens if you break the page into multiple dynamic
content display areas.
If
your website offers dynamic content and you wish to know the
details of what interests your online audience, a solution
purely using log file as a basis of your traffic analysis would
be insufficient. You may overcome this by a simple scripting
program included in your web pages. This program should identify
the user and capture the details of the page and content
identifiers and timestamp them as the user navigates through
your site. You may use the record unique identifiers from the
database for internal content. Using this information
consolidated with the results of your log file based analysis
would provide the details of what interest your online audience.
Personalization
is gaining importance. Collecting this information would also
help you to offer personalized content and customized navigation
to your online audience as their navigation patterns and
interests are known to the site.
Click-stream
Analysis
Click-stream
data can be explained as the pattern in which visitors navigate
through a site.
Log
files capture this information using the IP address of the
visitor. However, most of the solutions that I have come across,
do not offer any click-stream analysis.
This
makes your analysis one dimensional. In other words, you know
someone has looked at a particular page but you are not able to
see what else the same person has looked at.
What
does this mean in real life?
A
good example could be an affiliate program that you are using to
generate traffic to your site. Without the click-stream data,
you can tell how much traffic each affiliate is bringing to your
site. But you won't be able to delve into the details such as
the number of happy ending visits and the navigation patterns
and interests of the traffic brought to you by a particular
affiliate.
As
noted above, the click stream data is captured in the log file
or the solution recommended for the dynamic content can be
extended to collect click-stream data as well.
To
analyze this you would need a web site analysis tool that offers
multi-dimensional analysis. We are starting to see new solutions
emerging in this field. However, if you choose to collect the
data yourself as part of your web application, any OLAP tool
supporting multi-dimensional analysis would do the job.
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