What is remote card sorting?
Card sorting is a research method used to understand how people mentally organize information.
Rather than testing whether an information architecture is “correct,” card sorting helps reveal:
how users group concepts,
which relationships feel natural,
and how people interpret hierarchy and labels.
In remote card sorting with Lookback, participants sort cards using a drag-and-drop tool while speaking aloud, allowing researchers to capture both behavior and rationale as video-based evidence.
Why use card sorting in Lookback?
Card sorting is especially valuable when:
structure is unclear or contested,
internal assumptions differ from user mental models,
or navigation and labeling decisions carry long-term consequences.
Lookback adds value by ensuring card sorting remains qualitative, not just structural.
Instead of focusing only on final groupings, Lookback helps you understand:
why participants grouped items the way they did,
what they hesitated over,
where labels caused confusion,
and how confident (or uncertain) decisions were.
When to use remote card sorting
Remote card sorting is well suited for:
Information architecture decisions
Understanding how users expect content to be organizedWebsite or product navigation design
Testing category structures before committing to themConcept and feature grouping
Exploring how users relate ideas or capabilities to one anotherEarly structural exploration
When multiple valid structures may exist and tradeoffs matter
It is most effective when paired with think-aloud narration, rather than silent sorting.
How card sorting works in Lookback (conceptually)
Lookback does not provide a built-in drag-and-drop card sorting interface.
Instead, card sorting in Lookback is typically conducted by:
using a third-party web-based sorting tool,
and observing the participant’s interaction with that tool during a Lookback session.
This allows Lookback to:
record the participant’s screen and audio,
capture hesitation, confusion, and reasoning,
and produce session evidence that can be reviewed, clipped, and shared.
Setup details are covered elsewhere; the key point here is what you capture, not which tool you use.
Moderated vs unmoderated card sorting
Card sorting can be run in different ways, depending on your goals:
Moderated card sorting
Best when you want to:
probe reasoning in real time,
ask follow-up questions,
explore alternative groupings live.
The researcher can adapt questions based on what the participant does and says.
Unmoderated card sorting
Best when you want to:
reach more participants,
compare patterns across groups,
collect evidence asynchronously.
In this case, instructions should explicitly encourage participants to speak aloud and explain their choices.
AI moderation can be used to prompt clarification if needed.
Sample task prompts
Good card sorting prompts focus on reasoning, not just outcomes.
Examples:
“Organize the following items in a way that makes sense to you. As you do, explain why you’re grouping them this way.”
“If you were designing the navigation for this product, show how you would organize these categories — and talk through your thinking.”
“Group these topics based on how closely related they feel to you, and explain any items that were difficult to place.”
“Rank these features from most to least important, and describe what influenced your ranking.”
Evaluating card sorting results qualitatively
When reviewing sessions, focus on evidence, not just structure.
Questions to consider:
Did participants explain why they grouped items as they did?
Where did participants hesitate or change their mind?
Which labels caused confusion or reinterpretation?
Were there items participants struggled to place or felt were missing?
Did different participants use similar reasoning - or different reasoning for similar outcomes?
Look for patterns across sessions, not just agreement.
How card sorting fits with other methods
Card sorting often works best when combined with:
moderated usability testing (to see how structure performs in use),
interviews (to explore expectations and language),
or follow-up unmoderated studies to test revised structures.
Because all sessions produce the same type of evidence in Lookback, insights from card sorting remain connected to the broader Project.
Key takeaway
Remote card sorting in Lookback is not just about where users put things.
It is about understanding how users think about structure, and capturing that thinking as evidence - so decisions are grounded in observable reasoning, not just final layouts.