The Dirty Part of Web Analytics

By Melissa Kavanagh on July 31, 2008 11:25 AM | | Comments (0) | TrackBacks (0)
 

It might be cliche, but I have to say it - web analytics is a dirty job, but someone has to do it.


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When I say "dirty," I am referring to dirty data. There's a lot of it out there, and it is the web analyst's job to decipher the clean data from the dirty data and to figure out just what level of filth is acceptable.

What we sometimes encounter within any given web analytics tool are numbers that don't add up, don't make sense, and, sometimes, just don't exist.  Why is this?  There are a variety of tools available out there to help analyze web sites, such as Omniture's SiteCatalyst, Google Analytics, ClickTracks, Visual Sciences' HBX Analytics (recently bought by Omniture), WebTrends, Urchin, and many more.  The issue is that every tool has a different way of calculating the same basic metrics.

For example, one of the most common differences in calculations is in user sessions, or visits. What's the maximum length of inactivity in a session before a new session is counted?  If a user enters the site multiple times in a given time period, how many visits are counted?

In addition there are several technical issues that can cause data loss, such as the analytics code not having enough time to execute before a user leaves a page.  These technical issues can result in variances in unique visits, number of pageviews, number of form completions, revenue, etc.

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It's important to keep this all in perspective.  To quote the 2007 Web Analytics Shootout - Final Report, "If your yardstick measures 39 inches instead of 36 inches, it's still great to have a measurement tool. The 39 inch yardstick will still help you measure changes with a great deal of accuracy.  So if tomorrow your 39 inch yardstick tells you that you are at 1 yard and 1 inch (i.e., 40 inches), you know you have made some progress."

Web analytics can be best utilized for tracking search engine marketing performance and tuning, search engine optimization, online and offline campaigns, A/B testing, multivariate testing, and visitor segmentation.  It's important not to get hung up on specific numbers, but instead to look at the trends those numbers are showing.  The fact that your website received x amount of visits is nice to know, but it is more important to know whether your traffic increased or decreased during a given time period, or whether conversion rates have changed, find out what caused those changes, and to come up with an action plan to improve performance.

The bottom line is that web analytics packages are like any other tool, and when used properly can help you understand and grow your business. Web analytics can provide an outstanding ROI, and using web analytics properly will provide you with a major advantage over your competitors who do it less well.

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