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Posted by Steve Pugh on 11/19/47 11:40
JDS wrote:
> Hi, all. I am constantly butting heads with others in my department about
> the interpretation of web log statistics regarding viewership of a
> website. "Page views" "path through a site" "exit points" and that sort
> of thing.
Those things are useful if set up and interpreted with care, but are
not 100% definitive.
> On the web, there are two diametrically opposing views on the value of web
> server log stats.
>
> 1) Web server log analysis is very useful and can provide detailed,
> usable, accurate statistics
>
> AND
>
> 2) It can't
>
> Well, which is it?
Both.
> Typically, companies (e.g. Webtrends) that sell analysis software say
> the first.
Read the small print. WebTrends use cookies and JavaScript instead
of/as well as server logs. They have a number of products and services
which offer differing levels of accuracy. But at the end of the day
they can not be 100% accurate. Think of them as providing information
on general trends rather than precise detail on every user (if a user
has a static IP and/or accepts and keeps cookies and enables JavaScript
then you can study them very accurately).
> However, there are a number of articles pointing to the
> second. Notably, the author of "analog", one of the original web log
> analysis tools, says that you can't *really* get too much meaningful
> analysis out of your server logs.
Yes, Analog reads server logs alone. It doesn't try to do anything with
JavaScript, cookies, etc.
> Well, the problem that I see is that the articles pointing to the
> uselessness of web log analysis tend to be OLD. REALLY REALLY old in
> internet years -- ca. 1994 and 1995!
Server logs haven't changed.
> Now, technology has moved along since the WWW first hit the streets, so to
> speak, and my question(s) is(are) simple:
>
> What techniques exist to overcome the problems inherent in Web Server Log
> Analysis?
Cookies, JavaScript, guesswork.
> I know there *must* be some techniques! Things like tracking users via
> cookies and using "tracker" URLs (a server script that gets URLS and
> redirects the browser, thus writing a log of what was clicked and where),
> that sort of thing.
>
> If anyone can provide some insight on the following, that's be great:
>
> What techniques exist to improve Web Sever Log analysis?
>
> How good are they?
>
> What can I do to implement them?
>
> How do different log analysis tools compare? (Examples I have considered
> using are Analog, AWStats, Webtrends, and Sawmill.)
How much money do you have to spend?
Steve
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