Large publishing or informational websites pose problems for web analytics, because there is no clear “conversion”. These are sites which might have hundreds of thousands of pages, employing a vertical search to sort through their content. The business goal of the site might be to simply attract volume or drive people to look at banner-ads.

The site might be nothing more than a gigantic router, like Yahoo or AOL, incorporating news stories supplied through RSS feeds. Or the site might be purely informational, communicating information about products or services without much lead-generation or ecommerce (I’m thinking of big pharmaceutical company websites with thousands of prescription drug information pages). When it comes to web analytics, business groups in charge of these sites usually tell me that success on the site is measured in terms of the vague and nebulous “site engagement”.

Most of the web analytic tools out there claim that they can be tweaked to accommodate all-flash sites. They can. But with all they might hype about being able to track a Flash site just like a regular site – whether using a custom solution like Omniture’s Action Source or through embedded JS image-requests, I’ve found recently that there are certain key metrics that become untrackable in all-Flash sites. Rightly or wrongly, these metrics are also those which business managers often pay the most attention to.

Fact: Rich people drive more BMWs than poor people. But only a fool would conclude from this that driving a BMW will make you rich. Unfortunately, this is exactly the kind of logic many companies use to make business decisions regarding their web sites. Using advanced segmentation tools now so readily available, they chase what I call "epiphenomenal effects" and draw from them, at best, silly and, at worst, costly conclusions.

The basic idea behind segmentation is simple: Let's define a particular kind of visit or visitor and then look at the traffic and page-consumption patterns for these particular segments, comparing them against each other and/or looking for particular site features. Often, they result in findings like "a visitor of feature X is Y percent more likely to do Z on my site." Powerful analytical conclusions can be made as a result, and site optimization based on segmentation can have a dramatic impact on online business success.