Reading through Lown, Sierra and Boyer’s article from ACRL on ‘How Users Search the Library from a Single Search Box’ based on their work at NCSU, started me thinking about looking at some data around how people are using the single search box that we have been testing at http://www.open.ac.uk/libraryservices/beta/search/.
About three months or so ago we created a prototype tool that pulls together results from the Discovery product we use (EBSCO Discovery) alongside results from the resources database that we use to feed the Library Resources pages on the library website, and including pages from the library website. Each result is shown in a box (ala ‘bento box’) and they are just listed down the screen, with Exact Title Matches and Title Matches being shown at the top, followed by a list of Databases, Library Pages, Ebooks, Ejournals and then articles from EBSCO Discovery. It was done in a deliberately simple way without lots of extra options to manipulate or refine the lists so we could get some very early views about how useful it was as an approach.
Looking at the data from Google Analytics, we’ve had just over 2,000 page views over the three months. There’s a spread of more than 800 different searches with the majority (less than 10%) being repeated fewer than 6 times. I’d suspect that most of those repeated terms are ones where people have been testing the tool.
The data also allows us to pick up when people are doing a search and then choosing to look at more data from one of the ‘bento boxes’, effectively they do this by applying a filter to the search string, e.g. (&Filter=EBOOK) takes you to all the Ebook resources that match your original search term. So 160 of the 2,000 page views were for Ebooks (8%) and 113 f0r Ejournals (6%) for example.
When it comes to looking at the actual search terms then they are overwhelmingly ‘subject’ type searches, with very few journal articles or author names in the search string. There are a few more journal or database names such as Medline or Web of Science But otherwise there is a very wide variety of search terms being employed and it very quickly gets down to single figure frequency. The wordle word cloud at the top of the page shows the range of search terms used in the last three months.
We’ve more work to do to look in more detail about what people want to do but being able to look at the search terms that people use and see how they filter their results is quite useful. Next steps are to do a bit more digging into Google Analytics to see what other useful data can be gleaned about what users are doing in the prototype.