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Card sorting isn't a silver bullet

According to Sam Ng, card sorting is a great method for understanding users and validating classification systems. But card sorting has limitations. In this article, Sam Ng shares some hard learned lessons:

- Card sorting can easily get out of control if we try to cover too large information spaces at once
- People expect card sorting to create classification systems, but reality is that it doesn't give us all the answers we need to do so
- Analyzing card sort data is messy and there isn't necessarily a single correct answer.
- The best way of doing analysis is to eyeball data.
- Online card sorting tools reduce administrative overhead and makes iterative card sorts easier
- Card sorts should be carried out in iterative cycles, starting at a high level and then drilling down into specific clusters of content


  • Card Sorting: Mistakes Made and Lessons Learned Open link in new window

Henrik Olsen - September 17, 2007

See also: Card sorting (13) 



Thought you might be interested in taking a look at the card sorting case study that Donna Maurer just published on our behalf. It discusses the return on investment we helped Eurostar deliver last year via use of this method.

While it's difficult to separate the impact of card sorting from the impact of the other activities that made up this project, in the year since its redesigned site launched, Eurostar's online revenues grew from

Simon | September 25, 2007



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