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10.03.06
Measuring Internal Search W/ Functional Web Analytics
 By
Gary Angel
This is Part IX in an (epic) Series on Functional Web Analytics.
(A quick note - I'm in NY next week teaching a class on Functionalism at the WebSideStory
ActiveInsights Conference. If you're an HBX customer - I'm afraid you have to
be - and you're interested then go here.
"They Seek Him Here, They Seek him there - those Frenchies seek him everywhere…."
Like the Scarlet Pimpernel, good analysis of Search Functionality can be hard
to find. I just finished an excellent
post by Matt Lillig on his new analytics blog about looking at Internal Search,
and it inspired me to bump Search higher up on the ladder of Functional components
and talk about some of the peculiar issues associated with its measurement.
Matt's analysis focuses on the analysis of failed keywords - and pretty much everything he has to say is dead-on. It sounds like the site he was working on had extraordinarily bad performance in this regard. I don't think I've ever seen numbers quite so high for failed searches - and for a retail site bad search functionality is truly disastrous. This analysis of failed keywords is one of those very simple "checks" you have to do - it won't always or even often yield dramatic results but when it does the payoff is immediate and enormous!
I've found that there are three types of Search Analysis that are fairly common - and each is useful - though also limited in its own way. One is Matt's analysis of failed searches. This analysis is typically a slam-dunk in most web analytics solutions. It does, however, require that you pass the number of results returned on the search results page.
A second type of analysis focuses on successful searches - and is germane to a
certain kind of site - one for whom search is a fallback not a first option. For
sites that aren't search focused, it's often interesting to view what visitors
are searching on to spot holes in your navigation. For sites like this, what you
want to see is lots of search terms with very little percentage going to each.
When you see a search term getting a high percentage of total clicks, it's often
a cue that you should change something about your pages to cue visitors where
to find that information.
This technique, by the way, is increasingly problematic. We see many cases where
the visitors' first action is to Search - this being the default navigational
style for an increasing number of users. So for a growing segment of the population,
it doesn't matter what else you put on the site Search will be their likely navigational
choice.
Finally, Search is often analyzed in terms of endpoint conversion. In this regard,
Search is primarily viewed in comparison to non-search sessions - with designers
trying to analyze whether search sessions are more or less productive than browsing
sessions. This analysis is complicated for ad-based sites by the fact that search
sessions are nearly always shorter than browsing sessions. Conversion analysis
can also be quite interesting and useful - but it's necessary to put it into perspective.
In my last post, I described epiphenomenal effects - and Search can actually be
a prime example of this. On both retail and ad-based sites, the visitor who searches
often has a fundamentally different mind-set than one who browses.
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About the Author:
Gary Angel is the author of the "SEMAngel blog - Web Analytics and Search Engine Marketing practices and perspectives from a 10-year experienced guru.
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