methodatlas
RunsheetUX Research

Card Sorting

ComplexityLow
Time20-45 min
Participants5-15
FormatWorkshop + async
MaturityCanonical
01

Prerequisite

What needs to be finished first

Complete firstContent inventorynot in catalog

A list of pages, labels, topics, or items exists that can be grouped without mixing different levels of granularity.

Without: Without a stable item list, the sort becomes inconsistent and the results are hard to interpret.
02

Preparation

What needs to be ready before start

Materials

Card set or digital sorting board; label stickers or text cards; timer; notes for clusters and edge cases; camera or export tool.

People / roles

One facilitator; five to fifteen participants or test users; one observer or note taker; optionally one person who watches for label ambiguity.

Pre-read

Target audience, list of content items, and the decision to run an open or closed sort; any existing navigation or taxonomy assumptions.

Time needed

30-45 min

Setup

Prepare one card per item. Keep the wording short and consistent. Decide in advance whether participants create their own labels or sort into predefined groups.

03

Core question

The one question this method answers

How do people naturally group and label these items?

04

Flow

Marker: Minute

StepDurationActionHint
10-5 min
5 minExplain the item set, the goal, and the sort mode. Make sure everyone understands whether the sort is open or closed.If the sort mode is unclear, participants will invent different rules. State the mode before the first card is moved.
25-15 min
10 minLet participants move cards into groups or categories. Observe patterns, hesitation, and cards that are difficult to place.Do not guide the grouping too early. The point is to learn the user's mental model, not to coach the result.
315-25 min
10 minReview the clusters, ask for labels, and capture why certain items were grouped together or kept apart.Ambiguous labels are often more valuable than perfect agreement. Record the uncertainty instead of forcing a false consensus.
425-35 min
10 minCompare the results across participants, highlight stable clusters, and mark items with inconsistent placements.Look for patterns, not just majority votes. Repeated disagreements are clues for weak labels or a wrong taxonomy.
535-45 min
10 minTranslate the findings into navigation or label hypotheses and note which items need a second test such as tree testing.A sort result is a hypothesis, not the final IA. Always end with the next validation step.
05

Artifact

What comes out at the end

Form

Cluster map or card sort export with labels, stable groups, ambiguous items, and a shortlist of information architecture hypotheses.

Versioning / ownership

Record date, target audience, and sort mode. Keep separate versions for open and closed sorts, and note which items changed between runs.

Tool alternatives
  • OptimalSort
  • Miro or FigJam
  • Paper cards and a photographed board
  • Notion page with grouped content and labels

card-sorting-working-template.md

Compact working template for Card Sorting with context, input, output artifacts, and next step.

Card Sorting Working Template

Goal

Shows how users group and label content.

Context

When and for what do we use this method?

Input

Which data, observations, decisions, or materials are available?

Execution

Short notes along the runsheet.

Output artifacts

  • Content Groups:
  • Label Set:
  • IA Hypotheses:

Assumptions and open questions

  • ...

Decision / Next step

Owner, date, and success signal.

06

Example output

Concrete filled scenario, fictional example

card-sorting-beispiel.md

Concrete filled scenario, fictional example

Card Sorting — Help center content

Setup: 28 content items, open sort, 8 participants.

Stable clusters

  • Getting started
  • Billing and account settings
  • Troubleshooting and errors
  • Integrations and API

Ambiguous items

  • 'Notifications' moved between settings and troubleshooting.
  • 'Workspace members' grouped with account settings in 6 of 8 sorts.

Next step: Run tree testing on the top two label sets before updating the navigation.

07

Pitfalls

Recognize symptoms and steer against them

Trap

Items are mixed at different granularity

Symptom

Some cards are full pages while others are tiny subtopics, so participants cannot sort them consistently.

What to do

Normalize the item list before the session. One card should mean one comparable unit.

Trap

Open and closed sort are confused

Symptom

Participants start inventing labels in a closed sort or use predefined categories in an open sort.

What to do

Explain the mode clearly and show one example. The sort mode must stay stable from start to finish.

Trap

Too few participants or the wrong audience

Symptom

The result reflects only one team's internal language.

What to do

Use people who match the intended audience. If the audience is broader, run more than one session.

Trap

Labels are accepted too quickly

Symptom

The team writes a label and stops without checking whether it really fits the grouped cards.

What to do

Test every label against the items in the group. If it feels forced, rewrite it.

Trap

The sort is treated as final IA

Symptom

The navigation is changed directly from one card sort without follow-up testing.

What to do

Treat the result as a hypothesis. Follow it with tree testing or first-click testing before making structural changes.

08

Stop criteria

Done signals checkable in under a minute

There is no content inventory, so there is nothing stable to sort.
The target audience is unknown, so the language model cannot be judged.
Fewer than five participants are available, so the result stays too thin.
The task is about visual design, not information architecture.
The item list mixes pages, sections, and features, so the granularity is unusable.
No follow-up validation method is planned, so the result would remain untested.

Finished the runsheet?

Go to the profile for purpose, similar methods, and sources or continue to the next method in the catalog.