card-sort-analysis

Card sort analysis translates user grouping data into a prioritized information architecture by generating similarity matrices and grouping patterns to form a recommended navigation taxonomy.

Processing open and closed card sort data involves analyzing participant groupings to identify common categories and naming patterns, which informs a structured information architecture taxonomy.

Yes, you can use structured spreadsheet data from usability research to calculate item groupings and generate actionable information architecture recommendations.

A similarity matrix identifies how often items are grouped together, allowing you to extract common categories and output a prioritized information architecture structure with next steps like tree testing.

Yes, structured input data such as spreadsheets or raw card sort results is required to accurately calculate grouping patterns and produce a reliable navigation structure.

Card sort analysis accommodates varying participant counts and item sets, but requires accurately structured input data to identify grouping patterns and avoid noisy information architecture recommendations.