Card sorting

Card sorting is a method that reveals users' mental models: participants are given a set of cards (sections, topics, concepts) and asked to arrange them into groups as seems logical to them (open sort — they invent group names themselves; closed — by given categories). Analysis shows which items people combine, how they name groups, what they assign where. It is the basis for building a clear information architecture (948) — from how users think, not the team. Honestly about 'informs, does not dictate', this is key: card sorting gives valuable data about mental models but does NOT produce a ready structure automatically. The results must be interpreted and turned into IA — design work that also accounts for business logic, constraints, priorities. Card sorting is a powerful input, not a 'turnkey structure from a test'. Honestly about result ambiguity: different users often group differently — this is NORMAL (there is no single correct model in everyone's heads). Sometimes data gives clear clusters, sometimes blurry. We honestly work with this rather than pass off an average as the 'single correct' structure. Honestly about the sample: conclusions depend on the number and representativeness of participants; on a small/biased sample — limited conclusions. Honestly about the link: card sorting (how they would group) complements tree testing (954, whether they find in the ready structure) — together they validate IA. Honestly about the effect: it gives data for a structure from users, reducing the risk of an architecture 'logical for us but unclear for them', but it is an input, not a usability guarantee. Honestly about access: items for sorting and access to users are needed. An important boundary: this is card sorting (grouping); IA (design) — 948; tree testing (check) — 954. Picture this: instead of 'structuring by our logic' — data on how users think. The base price starts from 18,000 ₽ (depends on the number of cards/participants).

• The structure is built by the team's logic, not users'.
• It is unclear how people mentally group your topics.
• Section names are invented, not checked on users.
• The architecture is 'logical for us' but confuses users.

• Card sorting (open/closed) with users
• Analysis of groupings and group names
• Revealing the audience's mental models
• Interpretation into data for IA (948)
• Honest boundaries (informs, does not dictate; ambiguous results; depends on sample)
• A link with tree testing (954) for validation
• Accounting for business logic when turning into structure
• Handover and review with you

• Data on how users group information
• A basis for IA from users' mental models
• Less risk of a 'logical for us' architecture
• Honest boundaries (an input for structure; not a ready structure/not a guarantee)

• We prepare cards and select participants; run the sort
• We analyze groupings and names
• We interpret for IA, honestly set boundaries with you

• Will card sorting produce a ready site structure?

  No, honestly: it gives valuable data on how users group information but not a ready structure automatically. The results must be interpreted and turned into IA (948) — design work that also accounts for business logic, constraints, priorities. Card sorting is a powerful input, not a 'turnkey structure from a test'. We honestly do this interpretation step rather than pass off raw data as the final architecture.

• What if users group differently?

  That is normal, honestly: different people often group differently — there is no single model in everyone's heads. Sometimes data gives clear clusters, sometimes blurry. We work with this deliberately (look for stable patterns, account for business context) rather than pass off an average as the 'single correct' structure. Ambiguity is information, not a test failure.

• Does card sorting replace structure verification?

  No, honestly: it answers 'how users WOULD group', while checking whether they find what they need in the READY structure is tree testing (954). They complement each other in IA validation: card sorting at the input (forming the structure), tree testing at the output (checking it). We will honestly suggest what is needed for your task.