All too many of the ‘foofy’ web marketers would be quick to equate longer length of visit with ‘stickiness.’

I’m pessimistic… I’d be wondering if they were having trouble finding what they were looking for or experiencing slow page loads.

How can I tell the difference?

I guess I’d have to be able to see their navigation path through the site at the same time… how many pages did they browse? What kind of content were they browsing? What was their connection speed? How many times did they hit the back button? and so on…

What would I do with that information?

1.) I could track conversion rates a little better… how many times did I “get the click” like I hoped to?
2.) Are there any apparent navigation problems?
3.) Did someone just come from a competitors site?
4.) Did someone immediately leave to go to a competitor’s site?

Supposedly, CoreMetrics allows you to do this. It drops cookies on the user’s computer so that the analytics can keep track of the visitor’s path. We don’t use CoreMetrics but are considering it. Anybody else use CoreMetrics for any of this?

http://www.coremetrics.com/solutions/web_analytics.php

The biggest problem with LoV, as you stated, is that there’s very little you can actually infer from it. A longer average could either mean they’re interested or frustrated. A short time could either mean they couldn’t find what they wanted or they found it quickly. We’re then left with an almost meaningful statistic: medium length averages that we would expect.. but perhaps we see them as meaningful only because we’re looking for that particular range.

I would be more interested in how the LoV changes over the year. But, again, there’s very little we can infer without directly quizzing or, at the very least, observing the visitor.

What I would like to see, if there is such a thing out there, is something like Google Analytics’ “Site Overlay” whereby the statistics are laid out over your website. Then if we could change the statistic to the average length of time between coming to the page and clicking on a link. We could perhaps infer better whether the visitors are able to find the link they want quickly or whether they’re reading the content and clicking on links along the way. (For instance, a shorter length at the top and longer length at the bottom would infer that to be the case.)

Anyone know if there’s a tool like that out there?