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Log files contain loads and loads of information. Unfortunately,
most log file analysis tools only use a fraction of that information
and present the data in a way that's only exciting for accountants.
But there's new software on the market that seems ready to change
the way you feel about log file analysis forever...
Existing tools
Most existing analysis tools like
WebTrends
or Nedstat
generate pages and pages full of numbers and colourful graphics that
give information about:
- the number of visitors
- the most used browsers and platforms
- the most and least visited pages
- the most important entry and exit pages
Although all these numbers and graphic seem really interesting the first time you look at them, they very quickly get boring:
- The tools tell you what the most and least visited pages of your site are but they don't tell you why. They don't say anything about how people really use your site.
- After a while, knowing exactly how many daily or weekly visitors you have is really not all that interesting. Moreover, tests have proven that there are quite big discrepancies between the different analysis tools
(http://www.zdnet.be/kmoz.cfm?id=18423).
- It's only normal that people visit your site with different configurations. General data about most frequently used platforms, browsers, resolutions et cetera are widely available. You don't need a log file analysis tool to tell you that.
The ideal world
You're not just interested in the number of visitors and page views your site generates. You also want to know things like:
- How do users get to a certain page? Not only do you want to know where users go once they leave the homepage, you want to know from every page of your site how users got there. Which way did they follow on your site? Or perhaps they've come from outside? If so, which query have they typed in on Google to get to your site?
- What do users do after a certain page? Do they immediately buy the product? Do they have a look at other pages first? Or do they simply leave your site?
- Which links do users click on exactly? For example: on your homepage there are three links to your best selling product (a banner, the title of an article and an 'Order now!' hyperlink). Which of these do users click on most? Is there a connection between the type of link and the rest of the user's behaviour on your site? What if you change the title of a certain article; does that make users click more?
- What about your site's time efficiency? How much time do visitors spend on a page? How long did it take for them to get there?
- Do different groups of users use your site in a different way? Is there a difference between users who come to your site via Google and those who've clicked on one of your banners? What about the users who come to your site via a partner site; do they do what you expect them to? And what about the subscribers to your newsletter, what do they do on your site?
The answer: ClickTracks
ClickTracks is the perfect tool for everyone who's interested in knowing what users are really doing on their site. After importing your log files with one mouse click (ClickTracks automatically reduces these to about 1/100th of their
original size) you simply use ClickTracks to surf your site: next to every link there's a percentage that shows how many users have clicked that link.
In a second panel (on the right side of the image) there's information about the number of visitors, the length of the visits, the average time users have spent on your site before they got to this page et cetera. A third panel shows the users' path; which pages did they visit before this page and which ones after.
It only takes a few mouse clicks to put users together and investigate what different groups of users do on your site. Groups can be made based on ip addresses, cookies, the sites they come from, the query used to find you, a certain page they viewed on your site et cetera.
You don't have log files?
- Ask your hosting company to generate log files for you (They're supposed to that for you for free anyway).
- Try a free tool like JDTracker to generate log files.
Els Aerts & Karl Gilis
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