Ask every 100th visitorExpert suggests identifying the audience, instead of tracking numbers 1/07/2001 07:00:00 PM Eastern
As you're poring over your Web-audience-measurement reports, you're wondering: What to do next? Here's the start of answer: Maybe you shouldn't take those numbers as a definitive indicator of your Web-site performance, or base your Web strategy solely on what those numbers say.
That's according to Eric Meyer, an online journalism researcher and assistant professor of journalism at the University of Illinois College of Communications, who is, er, not your everyday ivory-tower type. Author of the strategic online publishing guide Tomorrow's News Today, Meyer is that rarest of multidiscipline breeds: an Internet content expert, a published authority on Web metrics, an owner/publisher (of two weekly newspapers in central Illinois), and, perhaps most impressive, a research scientist at National Center for Supercomputing Applications-the same University of Illinois-based institution that spawned the first widely distributed Internet browser.
In other words, Meyer is an expert and sees things from many different angles.
To borrow an ad slogan, Meyer thinks different. For example, rather than tracking how many page views your site has compared with a competitor's whose site may be organized quite differently, he suggests, it is more important to know who
your Web audience is and how it interacts with your site.
"Ask every 100th visitor a quick question: Why are you here? Bring them in to your station and chat with them about what they think of the site," he counsels.
Meyer has basic issues with the way Web metrics are researched and what news sites do or don't do with the numbers once they become available.
"You can't make an argument these are scientific numbers. There are serious problems with how the numbers are gathered. When it comes to panel-based research, we don't know whether our panels are representative," says Meyer, of the larger Internet audience. "Plus, when people are aware of the fact they are being monitored, we know that changes their behavior."
Some of the Web-traffic-measuring services note that the more they learn about Web-usage habits, the better they are able to make necessary tweaks in the way they count performance yardsticks, such as page views and "unique users." For his part, Meyer seems to think that, because the science of Web-audience measurement is still somewhat new, a "work-in-progress" factor is at play here that is important for people who run Web sites to understand.
"We don't know enough about online behavior yet, so we constantly change and adjust" the ways in which the Web-ratings services count Internet traffic. "Even within a given ratings organization, what they adjust this month might not have been what you adjusted last month," Meyer says.
"If you don't know what the causality factors are-such as 'do women and men surf the Web differently' and so 'should we be weighting our samples accordingly'-we don't know that," adds Meyer.
Meyer seems to tag Web metrics with a learn-on-the-fly label. "It's more market research than science, more superstition than science," he huffs.
To his credit, Meyer also has issues with the type of Web-site-management approach that articulates a site strategy and then makes a selective and oversimplified interpretation of some Web survey numbers to justify that strategy.
I asked Meyer about those television Web sites that justified their business plans for woman-centric content based on a couple of last year's surveys, which showed that women outnumber men on the Internet.
"You don't know where these women numbers are coming from. Plus, there are more women in society," he notes.
To this, Meyer adds a somewhat controversial but, to me, spot-on thought: If one argues that there isn't enough women-centric Internet content, while maintaining that more women then men use the Internet, then "whatever we were doing caused a great number of women" to become Internet users. In short, women flocked to the Web even before there was a great deal of content for them there.
"In research, they call this 'data mining,'" Meyer explains. He thinks that, if you base your business on assumptions without a clearly defined cause-effect factor, "it is considered a laughable strategy." Russell Shaw's column about Internet and interactive issues appears regularly. He can be reached at email@example.com