Web 2.0 Web metrics

Reviewing web metrics

Evan Williams (one of the makers of Blogger) posts a strong argument for why organisations should be moving away from using page views as a metric much in the same way we all moved away from hits in the late 90s.

Looking at MySpace he compares page views with ‘reach’ (effectively uniqiue visitors) and maps the results against the same for MySpace suddenly doesn’t look as far ahead as it did when based solely on page views. He draws on Mike Davidson‘s argument that MySpace has such enormous metrics largely as a result of poor architecture – requiring the user to go through refresh pages many more times than necessary if MySpace was redesigned from the ground up with usability in mind.

Ajax is only part of the reason pageviews are obsolete. Another one is RSS. About half the readers of this blog do so via RSS. I can know how many subscribers I have to my feed, thanks to Feedburner. And I can know how many times my feed is downloaded, if I wanted to dig into my server logs. But I don’t get to count pageviews for every view in Google Reader or Bloglines or LiveJournal or anywhere else I’m syndicated.

Another reason: Widgets. The web is becoming increasingly widgetized—little bits of functionality from one site are displayed on many others. The purveyors of a widget can track how many times their javascript of flash file is loaded elsewhere—but what does that mean? If you get a widget loaded in a sidebar of a blog without anyone paying attention to it, that’s not worth anything. But if you’re YouTube, and someone’s watching a whole video and perhaps even an ad you’re getting paid for, that’s something else entirely. But is it a pageview?

Pageviews were never a great measure of popularity. A simple javascript form validation can easily cut down on pageviews (and save users time), while a useless frameset can pump up your numbers. But with the proliferation of Ajax, RSS, and widgets, pageviews are even more silly to pay much attention to—even as we’re all obsessed with them.

2 replies on “Reviewing web metrics”

But I think using web metrics is just in its infancy with regards to museums. I understand the above argument to say that they are less useful for comparing the importance and impact of large websites such as MySpace and Blogger.

However, in museums that are starting to use networked web based information kiosks, web metrics can give you a whole new basket of info about how your visitors use your content. I have been stunned at the different ways that web metrics have allowed us to evaluate on the fly with our computer based terminals in the museum as well as on our website.

The availability of more complex analytics tools such as Urchin (now free as Google Analytics) will only improve this ability. I’m not really countering your post, just adding a different perspective on web metrics.

bryan kennedy
exhibit developer
science museum of minnesota, usa

hi bryan

I’d agree that web metrics are invaluable for analysing usage patterns, paths through sites, search phrases etc!

I guess the point is that some metrics such as the long-discredited hits and the incraesingly discredited page views are not good measures of usage.

On our external sites we steer away from page views now we use AJAX on our collection search and instead look at objects viewed and searches undertaken – which are far better indicators of actual usage when combined with visits and unique visitors.

On our internal web kiosks, we have to use page views instead of visits to get a rough idea of usage, and this means we still have difficulties in working out how many individual people are sitting at the kiosks using them because they are logged with the same IP address in the logs and sometimes the time between visitors using them are too short to register as seperate sessions (even when we use session variables).

Also, as we are a public institution we have to report basic analytics to government every month who, I can assure you, do compare our results with other organisations – except there is no mandated analysis package (such as Google Analytics, Web Trends or AWStats) across all reporting organisations which means everyone’s stats are collated in different ways.

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