Search Behavior: I Don’t Know What I Want, or Where to Find It

First published July 31, 2008 in Mediapost’s Search Insider

In my last two columns, I looked at how search plays a part when we’re in two information gathering states: I know what I’m looking for and where to find it; and, I know what I’m looking for but not where to find it. Today, I’ll look at what happens when we don’t know what we’re looking for or where to find it.

In the first two states, our intent is pretty well defined. We’re looking for a piece of a puzzle and we know the shape of that piece when we see it. In information-foraging terms, we’ve already defined our diet. It’s just a question of which patch we look in. When we extend that to search engine usage, we have already defined our query, and it’s just a question of how we interact with the results page. In both these states, search engines work pretty well.

The Missing Puzzle Piece

But what if we have no idea what the puzzle piece looks like. We don’t know the shape, we haven’t assembled the adjacent pieces and we only have some vague idea what the finished picture should look like. This is the ultimate challenge for online search, and one that all search engines have largely failed to meet until this point. This is where we need a guide and advisor, a connector between ourselves and the universe of potential knowledge available. Because our knowledge is imperfect, we need a sage whose knowledge is perfect — or, at least, much less imperfect than our own.

Of Disambiguation, Discovery and Berrypicking

This is where three concepts play an important role: the need to disambiguate, the thrill of discovery, and a revisit of Marcia Bates’ concept of berrypicking. Let’s begin with disambiguation.

When we have no idea what we’re looking for, we don’t know how to define it. We don’t know the right query to present to the search engine. The more imperfect our knowledge, the more ambiguous our query. This is where search needs better knowledge of who we are. It needs to know — through implicit signals such as our areas of interest, our past history and our social connections –what it is we might be searching for. If a search engine is successful in lending more definition to our query, it stands a chance of connecting us to the right information.

The second piece is discovery. If a search engine is successful in introducing potentially relevant information to us, our interaction is quite a bit different than it is in the first two information gathering states. We spend more time in our interaction and “graze” the page more. We’re also open to more types of content. In the first state (know what we want and where to find it) we’re just looking for the fastest navigation route. In the second state (know what we want but not where to find it) we’re looking for confirmation of information scent to judge the quality of the patch. But in the third state, we could be enticed by a website, an image, a news story, a video or a product listing. We’re pretty much open to discovering anything.

And this brings us back to Bates’ theory of berrypicking. Because we have no preset criteria for the type of information we’re looking for, we can change direction on the turn of a dime. In our pursuit, we fill in the definition of our prey as we go. We follow new leads, change our information-gathering strategies and sometimes completely change direction. Our interactions with search turn into a serendipitous journey of discovery. It is in the third state where our patience is generally higher and our scanning pattern the broadest. Any cues on the page that trigger potential areas of interest for us, including brands or cultural references, could catch our attention and lead us down a new path.

Search Pursues Discovery

It’s this type of search that Ask’s 3D interface or Google’s Universal results set was built for. It’s also the thorny problem of disambiguation that has spawned a number of approaches, from Google’s exploration of personalization to the human assisted approaches of ChaCha and Mahalo . Even Yahoo’s Answers is a discovery tool, using the more natural approach of question and answer to lend some definition to our information quest. But even though we are defining our criteria as we go, we still seek to conserve cognitive energy. We have a little more patience in our seeking of information scent, but just a little. We still spend seconds rather than minutes looking for it, and because search is still trying to get discovery right, our sense of frustration can mount rapidly. We’re still a long way from finding a universally satisfying online source for discovery.

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