Card sorting

Card sorting is a qualitative research method used to group, label, and describe information more effectively, based on feedback from customers or users.

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Why use card sorting?

Most commonly, card sorting is used when designing (or redesigning) the navigation of a website or the organization of content within it. And that’s because it helps to evaluate information architecture—or the grouping of categories of content, the hierarchy of those categories, and the labels used to describe them.

Card sorting is useful if you’re trying to: 

  • Increase the findability of content on your website
  • Discover how people understand different concepts or ideas
  • Find the right words to form your navigation
  • Adapt to customer needs and surface the most important information

What are the different types of card sorting?

Card sorting requires you to create a set of cards—sometimes literally—to represent a concept or item. These cards will then be grouped or categorized by your users in ways that make the most sense to them. For best results, you’ll need to decide if it makes sense to run an open, closed, or hybrid card sort. There’s a case for each:

  • Open card sort: participants sort cards into categories that make sense to them and label each category themselves
  • Closed card sort: participants sort cards into categories you give them
  • Hybrid card sort: participants sort cards into categories you give them but may also create their own categories if they choose to

Which one you choose will depend on what you want to find out and what you’re already working with.

Is card sorting qualitative or quantitative in nature?

In it itself, card sorting is a quantitative process. The main quantitative data output from a card sort is a set of similarity scores that measures the similarity of how users grouped their sets of information. In other words, if all users sorted two cards into the same pile, then the two items represented by the cards would have 100% similarity. If half the users placed two cards together and half placed them in separate piles, those two items would have a 50% similarity score. So on and so forth. Additional quantitative data, like the time it takes to complete, is also available.