OptimalSort

(guest post by Michelle Kang and Raji Keluskar)

Card sorting is an effective, easy-to-use method for understanding how people think about content and the way it’s categorized—it helps you organize information that is easy to find and understand. As students in the Information Architecture class, we were generously offered a free trial of the Optimal Workshop’s card sorting product called OptimalSort. As a class of seven, we used this as a part of our assignment to learn about the labelling systems by each of us making an open card sort consisting of 30 cards based on different topics and acting as participants for each other’s.

While we were using the online OptimalSort, we noticed how it is more user-friendly and flexible than the method of using physical Post-its. Having the ability to put together questions to screen participants was something we found very convenient. Although we did not need to use this tool in our assignment, it is a tool that we feel which distinguishes OptimalSort from the traditional Post-it card sorting. Being an online platform, it allowed the participants to take part at a time most convenient for them while the sort was open and the “unique study link” can be shared via email and other platforms to recruit more participants. Users may also choose to use the integrated participant recruitment which holds a recruitment panel of 10 million participants all over the world with 70+ languages.

OptimalSort not only helps users during the card sorting but also presents them with an accurate analysis report of all the sorts that you conduct assists in gaining clarity and the confidence to make informed decisions. Being able to have a see in the analysis of each card sort by individual participants, cards, and categories through the features such as the similarity matrix, dendrograms and participant-centered analysis helped our class gain a grip on the ambiguity of language in labelling and categorization. The option to exclude the information of the participants who decided to abandon the sort before finishing prevented the possible problem of having inaccurate data in the overall overview summary and analysis.

On behalf of our DD37 class, we would like to thank Optimal Workshop for allowing us to experience these highly functional features that top notch companies such as NASA, Google, Netflix, Autodesk, BBC, NatGeo and thousands more, use to enhance their products on daily basis. Thank you!

Leave Comments