Search: weigh or eliminate?
A couple of years ago I reviewed a book by web usability experts 37 Signals called Defensive Design for the Web in which they gave side by side examples of how to do web shops right and how to do them wrong.
One of the examples had two sports stores go head to head. Both let you search for basketball shoes, but one (the bad one) showed you all hundred or so results at once, while the other (the good one) let you use filters to help you further narrow down your search. For instance you could say: only show me the sneakers with black laces, or the ones that cost less than 100 USD.
Both methods though, the one that showed all the results at once and the one that let you use filters, had an underlying assumption that all search criteria are equally important. Perhaps this is a side-effect from the success of Google. Search has become so relevant—and therefore successful—that we apply the same assumptions about search everywhere. This is what search should be like, we say.
VU researcher Frans Feldberg begs to differ though (Dutch). He claims that online stores would be better off using a mixture of regular and weighted filters. His 2006 research into automated decision support systems seems to indicate as much. Unfortunately all the weighted support systems cannot help you if your search yields no results—I couldn’t find out what his paper is called, or I would have linked to it.