Card sorting data analysis
Learn how to sort and analyze card sorting data to inform information and content organization decisions.
Sorting and analyzing card sorting results
Once all of your card sort results are in, it’s time to sort and analyze the data. These results can be:
Qualitative: The responses participants give to follow-up questions and the categories they define and label.
Quantitative: Which cards appeared together most often, and how often cards appeared in specific categories.
Most remote card sorting tools will include built-in reporting to help you sort and analyze your results. Begin by reviewing the results at a high level. Try to find common patterns in how the cards are sorted and (for open card sorts) the category names that are provided.
If you conducted an open card sort, take some time to review and standardize categories with similar labels – look for different spellings, capitalizations, and wording. Be sure to look at both the category label and the cards in each category to make sure your participants are thinking similarly.
On Lyssna, an agreement matrix shows the percentage of participants that placed each card into a category.
And for open card sorts, a similarity matrix shows how often pairs of cards are sorted into the same category, regardless of which specific category they were sorted into.
When reviewing your data, look for clear clusters. How frequently are cards placed in certain categories? Are there any outliers? Identify cards that are spread across multiple categories. This will help you to identify the different mental models of your participants, for example, participants who sorted household products by type versus by room.
After running an open card sort, define a list of categories based on your observations and validate these results with a closed card sort.
By now you should have valuable insights to share with your team about your target audience, and can make confident decisions about structuring the content on your site.