After participants complete your card sort, you'll see aggregated results showing how participants grouped your cards into categories. This data helps you understand how users naturally group and categorise information.
Cards & categories analysis
Switch between the cards and categories tab views to analyse your results:
Cards: Shows each card and how participants categorised it
Categories: Shows the categories setup in builder or participants created and which cards participants have sorted into them
Cards
Card: The card labels used in your card sort
Number of categories: How many different categories participants placed this card into
Consensus: Consensus shows how much people agreed on where this card belongs. If most placed it in the same category, the score is high. If people split it across categories, the score is lower.
Category breakdown:
Categories: The specific categories each card was sorted into
Frequency: The amount of participants that sorted the card into the category
Agreement rate: The percentage of participants who agreed on the category placement
Categories
Category: The category labels used in your card sort or categories created by the participant
Number of cards: How many different cards were placed in this category
Consensus: Consensus shows how much people agreed on the cards in this category. If many cards were placed here with strong agreement, the score is high. If cards were uncertain or spread out, the score is lower.
Card breakdown:
Cards: The specific cards sorted into the category
Frequency: The amount of participants that sorted the card into the category
Average rank: The average rank position the card was placed within the category
Agreement rate: The percentage of participants who agreed on the card placement
Category Standardisation
Standardisation tools help you clean up and analyse your card sort results by combining similar categories and renaming inconsistent labels. This is especially useful for open and hybrid card sorts where participants create their own category names.
Why standardise categories?
Common naming variation: Participants often create categories with similar meanings but different names e.g. "Navigation" vs "Site Navigation" vs "Menu"
Improved analysis: Standardising these variations gives you cleaner, more accurate results by grouping conceptually similar categories together. The changes you make to category names and combinations will be reflected in the analysis matrixes in card sort results.
How to standardise categories
Rename categories: Click on any category name to edit it. When you rename a category to match an existing category name, they will automatically combine and merge all card data. You'll see a confirmation dialog before this happens.
Combining specific categories: Select the checkbox beside the categories you want to combine and click the ‘Combine categories’ button this will open a dialog showing the category selections and sorted cards to review before combining.
Hide and show categories: Use the hide option to temporarily remove categories from your results table and visualisations. This is useful for filtering out irrelevant categories or focusing analysis on specific groupings without permanently deleting data.
Reset combinations at any time: If you make a mistake, you can reset category combinations to return to the original participant-created categories at any time.
Agreement Matrix
The Agreement Matrix shows the percentage of participants who placed each card into each category, helping you understand how consistently participants grouped specific items and which categories attracted the most agreement.
Understanding the agreement matrix
Rows: Individual cards from your card sort
Columns: Categories that your or the participants created
Agreement rate: What percentage of participants placed that specific card into that specific category
Color coding
Dark blue/high percentages (80%+): Strong consensus, most participants placed this card in this category
Medium blue/moderate percentages (40-79%): Some agreement, participants were split on where this card belongs
Light blue/low percentages (<40%): Little agreement, few participants placed this card in this category
Similarity Matrix
The Similarity Matrix shows how often participants grouped pairs of cards together in the same category, helping you identify which items have strong relationships and natural associations in participants mental models.
Understanding the similarity matrix
Each card appears with percentage values showing how often it was grouped with other cards
High percentages (80%+): These cards were frequently placed together by participants
Low percentages (<40%): These cards were rarely grouped together
Individual responses
This is where you will find the results for each individual participant.
Duration: How long it took the participant to complete the task
Cards sorted: the percentage of cards the participant sorted into categories (If it is not a requirement to sort all cards)
Categories created: Amount of categories created by the participant (If participants are able to create new categories in Hybrid or Open sorts)
Completion date: The date and time the participant completed the study
Click on any individual response in the table to view the recording. The recording will include the screen, camera and microphone recording if it was enabled in the build settings.
