Card Sorting- Information Architecture Technique

Information Architecture Technique
Card Sorting

Why use Card Sorting
Method for Addressing Problems of Find-ability

Product Team asks, 
‘Where does this piece of content or functionality belong?’
 
UX Team asks, 
‘Where would the user START this task?
 
User asks, 
‘Where do I find what I’m looking for?’
Problems of Find-ability

What is Information Architecture?

5 Planes of User Experience
Skeleton
Scope
Strategy
Surface
1
2 3
Structure

Skeleton
Scope
Strategy
Surface
1
2 3
Structure
5 Planes of User Experience
Information
Architecture

• Each piece of content or functionality is converted to a ‘Card’
• Cards are organized into groups by participants
• Participant’s responses are analyzed to better understand the user’s
mental model
• Analysis provides recommendations for improved organization, labeling,
and find-ability
Card Sorting Overview

Each ‘Card’ consists of:
• Name
• Description
• Fit Confidence 
Perfect, Good, Fair
• Importance (optional) 
Very Important - Not Important
Card Sorting Overview

Two Primary Methods
Open Card Sort vs Closed Card Sort

Closed Card Sort
• Used when you know the group
names.
• Quantitative method used for
validation of group names and the
placement of items within those
groups.
Two Primary Methods
Open Card Sort
• Used when you do not know the
group names.
• Qualitative method used for
generating insights into group names
and user mental models.

Phase 1
• Mix the cards up and hand them to a participant.
• Ask them to group each card with other cards they feel it fits with.
• Ask them to use the think out loud method and to mark any annotations on the cards. 
Pay special attention to the mental model the participant uses to group items, and the
alternate names and descriptions they write. 
Is it by frequency, relatedness, something else?
Open Card Sort - Method

Phase 2
• For each group, have them go through each card and select the fit confidence. “How well
do you think X fits in this group?” 
Have them also select the “Importance” of each card (optional).
• Then, ask each user to come up with a name for each group. The group name also helps
drive insights.
Open Card Sort - Method

Shows how often an item was
grouped with another item,
factoring quality of fit.
Analysis - Similarity Matrix / Contour Map

How to construct using Excel:
• Each sheet is a new participant’s matrix
with a total sheet which sums the cell
across participants.
• For each cell, if the two items were in the
same group, average their fit confidence. 
e.g. If Item A was a Perfect Fit and Item B
was a Good fit, mark a 2.5 in that cell.
• Note: A Perfect has a value of 3, 
good has a 2, and fair has a 1.

• Use Conditional formatting with a Graded
Color Scale
• Sort columns to try and group darker
colors together into ‘clusters’
• Note: The Row and Column are
transposed, i.e. if you move a column, you
must move the row as well.

Shows the relationship between
features.
Larger the height, less connected the item. 
e.g. 11 and 12 are tightly connected. 
15 is loosely connected to16 and 17.
Analysis - Dendrogram based on Cluster Analysis

How to Use:
• Use this as a starting point to find logical
groupings, based on height.
• Consider the number of groupings
participants created.
• Remember, this is the result of qualitative
data, not quantitatively significant data.

Example of 5 Groups, 
Based on height.

Based on height.

How to construct using Past 
(or other statistics software):
• Use the data from the Similarity Matrix
• Multivariate -> Clustering -> Classical
Hammer, Ø., Harper, D.A.T., Ryan, P.D. 2001. PAST: Paleontological statistics software
package for education and data analysis. Palaeontologia Electronica 4(1): 9pp.
https://folk.uio.no/ohammer/past/

Method 1
• Similar to the Open Card Sort Method with one exception.
• Create Pre-defined Header Groups which the participants place cards into.
Closed Card Sort - Methods

Method 2 - Survey
Create a survey where each item has a
single selection of each group name.
For each item, capture attributes such
as importance or confidence
(optional).
Closed Card Sort - Methods

Closed Card Sort
Method 2 - Analysis

Shows the percentage of
participants that grouped an item
into a particular category.
Analysis - Correlation Table

• For each cell, calculate the percentage of
participants that selected an item for
each group compared to other groups.
• Color code based on the percentages.
• Green highlight indicates the highest percentage
each item received.
• Red highlight indicates percentages over the
margins of error (e.g. 10%) that were not the highest
percentage for that feature. This indicates lower
agreement.
• For each group, sort based on the items
that contained the highest percentage

Shows the average importance participants assigned to each item. 
The higher the value, the more important it is to the participants.
Analysis - Item Importance Chart (optional)

Show how items were placed
between the initial proposal and
the result of the Close Card Sort.
Results

• If problems of find-ability exist, Card Sorting can solve these pain points
• To gain insights into those pain points, use an Open Card Sort method. 
To validate pain points or solutions, use a Closed Card Sort method.
• Analysis of a Card Sort will help craft better item names or groupings.
• Better naming and grouping will increase the use of features or content.
• An increase in the use of features or content provides business value to
the organization, which can be validated through analytics.
Summary

Card Sorting- Information Architecture Technique

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