Making Recommendations
You may want to summarize your analysis for your client/department as well as provide them with your raw data. One way to do this is to create a recommended list of categories based on your open card sort analysis, and suggest that they be tested in a closed card sort. You may also want to provide some detail concerning each category's performance in the card sort. Your recommendation document may look something like this:
Library Open Card Sort
Categories Recommended for Closed Card Sort
Data Analysis
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The majority of users placed the “About Us”-themed items into a category titled “About the Library”.
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All of the participants placed the personalized items into a “My Account” or “My Library” category.
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The overwhelming majority of Collections-themed items were placed into a “Collections” or “Special Collections” category by participants.
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The majority of Online Resources items fell into the “Online Resources” category, including the RSS Feeds item.
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The overwhelming majority of Event items were placed into an “Event” category.
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The Programs & Services items fell mainly into the “Programs & Services” classification, with 1/3 placing the Interlibrary Loan and Ask a Librarian items elsewhere into the “Online Resources” category.
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There was a general lack of consensus concerning features such as Suggested Authors, Hot Titles, Teen Reads, and Pathfinders.
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