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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.
The new version of our mobile search for our library website went live earlier in the week. This uses the Ebsco discovery API to access licensed resources. There’s a screenshot on the left as access is I’m afraid limited to OU students and staff. The new version owes a lot to the work of the developer on the MACON project and has been adapted by our library website developer (@beersoft). Access to be mobile version can be gained from a link on the bottom right of the desktop version or by autodection if you are already on a mobile device.
New features include showing the last five items that you have viewed as well as your last ten searches. These are features that are thought to be particularly useful for mobile users as the less time spent fiddling around with retyping URLs or search strings the better. The feature also includes access to an advanced search screen that allows Keyword, Author, title, Published after and Published before searches.
Search results appear within the interface with the search words highlighted. You can choose to have 10, 25 or 50 results per page. Links to the item take you to the EBSCO interface, or, if there is a DOI, to the publisher website via an EZProxy link. It looks like a nice step forward with the search system and it’s good when work that is strongly influenced by work from projects like MACON and RISE gets through into service.
I’ve been trying to find the time to do a bit more work on the library search terms I was looking at earlier http://libwebrarian.wordpress.com/2011/04/01/library-search/ So here a bit later than I hoped are a few more thoughts based on what search terms people have been using. The data comes from search terms used by people searching via the tabbed search box on the library website homepage, so they have the option to search the library catalogue, library website, and our e-resources system, Ebsco Discovery Solution. I’ve also looked at an equivalent set of search terms from the predecessor of EDS, 360 Search.
Don’t put text in the search box
Whenever we’ve put ‘helpful’ text into the search box then those words become the most searched for term, by a considerable margin. So ‘Search the Library Catalogue’ is ten times more likely to be submitted as a search term than the next highest term. ‘Search One-Stop’ is five times more likely. That implies users have just been clicking on the Search button. One of the explanations that has been suggested is that it offers them a quick way to get to the underlying search system.
At the moment we’re testing stopping users being able to click search until they’ve entered some search terms and not putting any text in the box to gauge user reactions.
Cross-over of terms between different search tabs
I’ve done some more work on looking at the top 100 search terms to compare what users type into the catalogue, website, federated search and discovery search boxes. When I looked at the top 20 then approximately 40% of the search terms were identical across the search platforms.
Unsurprisingly that changes when you look at the top 100. Only about 22% of the search terms are the same across all the search boxes, with 45% used in at least three search boxes. The graph below refers.
There are a couple of figures that seem to stand out. 41% of website search terms have only been used in the website search, and that’s understandable. But at the opposite extreme only 16% of search terms used in the catalogue search are unique to the catalogue. That may be a peculiarity of a distance learning institution that there’s less unique print content maybe.
As well as the search terms we’ve also got the number of times each of the terms have been used. This gives a slightly different picture
There is quite a big drop off after the top 10 searches in terms of numbers of searches. The top 10 are in the 100s and there’s quite a long tail. So because a high proportion of the top 20 results are used across all search tabs then when you add up the total search numbers it pushes the percentage up much higher than when you just count the search words.
Again the catalogue has fewest unique searches, but federated and discovery search all have more unique searches than the website, which is a little curious. I’d have expected there to be considerable common ground between federated and discovery search and for them to have many similar terms. That bears some further investigation.
Direct comparisons of the different types of search
I’ve included graphs below of each of the four search types comparing the percentages of search words with search numbers. In each case the graph looks at the list of search terms seen by that search system and then compares them with the other search terms to show whether they are common to 1, 2, 3, or 4 search lists.
Using the numbers of times the search terms are used is to my mind more representative of what users are searching for. That gives a pattern that says that more than half of the time users are using the same terms in each search box. Although you’d expect that cross-over between federated and discovery search, and to maybe a lesser extent, the catalogue, you wouldn’t expect it with the library website as it contains mostly help and support materials or information about services.
That seems to me to imply that:
- Users aren’t all that clear what the different tabs are searching. Website in particular is an ambiguous term. You couldn’t really argue with a user that insisted that they are all websites anyway.
- There’s a lot of common terms that could equally (and legitimately) be used against most (if not all) of the search tabs and users might well expect (and want) useful results
- That if users are going to type the same search term into every box then it would save their time (isn’t that one of Ranganathan’s laws?) just to let them type it once.
It’s been an interesting exercise and some useful evidence to compare alongside our search evaluation and focus group work to feed into our website redesign project.