DR
A CRM-FOCUSED COMPANY
Problem:
A Customer Relationship Management (CRM)-focused company recognized the need to enhance the clarity and organization of their software's content structure. Their goal was to gain insights into how users naturally classify and group information to improve the overall end-user experience.
During this project, I collaborated with three colleagues to independently facilitate card-sorting activities and analyze the resulting data.
DeKita is highly effective leading studies on her own from kick-off to delivery of insights, but also work beautifully on a team with other researchers and cross functional teammates. I get to personally witness Dekita's ability to fit into any role that was asked of her.
- Research Manager
Actions:
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Conducted two 1-hour card sorting activities via Optimal Sort :
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Sorted 26 cards representing third-level menu topics into the existing 8 second-level menu categories.
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Sorted 16 second-level category topics into 3 top-level menu categories.
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Analyzed qualitative data using Participant-centric analysis (PCA) to develop mental models for each card sort. Applied statistical analysis to associated topics and the suggested labels for information architecture (IA) groupings.
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Co-created and co-presented a comprehensive 40-slide deck report, including an executive summary and detailed findings.
Results:
I provided recommendations on category organization, grouping logic, and label clarity. I presented the proposed information architecture (IA), agreed upon by the majority of participants, along with an indication of categories that differed from the tested IA (current structure). I Included an analysis of category and card names, highlighting participant interpretations of labels and identifying confusing or unclear elements.
What I learned:
Discovering the nuances of my first industry card sorting analysis required navigating a learning curve. This experience prompted the need to quickly navigate the intricacies of the process, enabling me to derive meaningful insights from the collected data. Overall, I gained a profound understanding of how this research and analysis is conducted.
I also learned how crucial it is to have a comprehensive understanding of the website's structure and content before conducting card sort activities. It is good to come at it with an open mind as a researcher, , but equally important is recognizing that participants' perspectives may reveal nuances and preferences that were not initially apparent. Balancing a solid understanding of the website's intricacies with the flexibility to adapt and refine based on user feedback allows for a more collaborative and user-centric approach to optimizing information architecture through card-sort activities.
Bias can be reduced in card sorting activities by modifying the arrangement of the cards and labels.