A Pew Internet & American Life Project study about search engine users indicated that the vast majority of them expressed satisfaction with their search skills. According to the study, 92% of those who use search engines say they are confident about their searching and 87% of searchers say they have successful search experiences most of the time, including some 17% of users who say they always find the information for which they are looking. Now if most Americans are using Google to find the latest information on Paris Hilton or the Academy Awards ceremony, I imagine they find what they need. But in the event they don’t immediately and easily find what they seek, some poor search behavior is likely to emerge.
In his Alertbox newsletter, Jakob Nielsen shared the results of research that indicated that while search users have better skills now than they did five years ago, when their first efforts fail most searchers are incredibly bad at finding, and that’s typically because they don’t know how to search. According to Nielsen, users face three problems:
* Inability to retarget queries to a different search strategy (i.e., revise the strategy)
* Inability to understand the search results and properly evaluate each destination site’s likely usefullness
* Inability to sort through the SERP’s polluted mass of poor results, to really address whether a site meets the user’s problem (SERP=Search Engine Results Page).
As academic librarians we assumed that end-users only had trouble with our catalogs and library databases because they were oriented to librarian-style searching (which only appeals to librarians), and that making all library databases more like search engines in order to facilitate finding (which is what everyone else wants to do) would bring about a new golden age of end-user information retrieval. I see two significant flaws in that vision. First, end-users clearly have a hard time finding information on ultra-findable Google if their first effort fails, and second, the solution to the first problem is better search skills – the type of skills that librarians use to find information. Neilsen refers to current end-user search behavior as Goggle Gullibility because:
many users are at the search engine’s mercy and mainly click the top links. Sadly, while these top links are often not what they really need, users don’t know how to do better.
And while finding processes can sometimes be simple, at other times they are, according to Louis Rosenfeld, quite circuitous, iterative and surprising. In other words, finding involves a fair amount of searching. In fact, Rosenfield’s finding formula is “browse + search + ask = find”. That’s why we need to develop search systems based on the knowledge that there “is more than meets the eye when it comes to the process of finding” and not simply on an assumption that finding is simple, intuitive and completely different from searching. Searching is an integral part of finding. Searching involves decision making, and so does finding. Searching does assume more of a plan of attack, while finding suggests a more carefree and random approach. But as Rosenfield points out, “most of the systems we design don’t really support finding.” I’ll take that to mean both web search engines and commercial library databases.
Finding, as Rosenfield puts it, “is arguably at the center of all user experiences.” I agree. Everyone wants to find, both end users and librarians. But until systems better integrate browse, search and ask functions it’s highly unlikely that finding will be the simple, mindless task we think is an end-user’s version of search. Rosenfield thinks the answer to better finding is web design based on analytics. Studying users’ behavior and understanding what they are trying to accomplish is a well traveled path to creating better user experiences. The more we know about our users’ behavior when they search our systems, the better we can do at anticipating their needs and structuring search systems that facilitate their finding. This is especially true for our complex library websites where enabling finding is a challenge. As I’ve written previously, I think what we all want is to “create,” and both searching and finding are means to that end. I prefer “search first, find, and then create.”