Mining internal search engine data

We do some limited of search terms on CTSI web properties, but this is a big gap, per user experience author Lou Rosenfeld in his new book Search Analytics for Your Site. Rosenfeld’s the author of the seminal Information Architecture for the World Wide Web, so when he speaks, I tend to pay attention. An interview in O’Reilly Radar digs into the details of what analyzing search data in internal search engines and systems:

“[Site search isn’t] necessarily overlooked by users, but definitely by site owners who assume it’s a simple application that gets set up and left alone. But the search engine is only one piece of a much larger puzzle that includes the design of the search interface and the results themselves, as well as content and tagging. So search requires ongoing testing and tuning to ensure that it will actually work.

“[Site search analytics Does SSA reveal user intent better than other forms of analytics?
I think so, as the data is far more semantically rich. While you might learn something about users’ information needs by analyzing their navigational paths, you’d be guessing far less if you studied what they’d actually searched for. Again, site search data is the best example of users telling us what they want in their own words. Site search analytics is a great tool for closing this feedback loop. Without it, the dialog between our users and ourselves — via our sites — is broken.”

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