Product design skills

references/analysis.md

A supporting file of the ia-evaluation skill.

IA study analysis

Card sort

Similarity matrix

For each pair of cards (a, b): similarity(a, b) = participants who placed a and b in the same group / total participants. Display as a matrix ordered so high-similarity pairs sit together (most tools do this; by hand, sort by the strongest pair first and grow the cluster).

Clustering

Agglomerative clustering on the similarity matrix produces the dendrogram. Read it at a chosen agreement level (60-70% is the usual first cut): each branch below the cut is a candidate group. Lower cuts merge groups; higher cuts split them. Report the cut used.

Standardisation

Participants name groups differently. Before counting labels, merge synonyms into standardised categories ("Billing", "Payments", "Money" -> "Billing and payments") and keep a map of original wordings with frequencies; the most frequent user wording is the label candidate.

Reporting

  • Strong clusters: cards with pairwise similarity above the cut.
  • Contested cards: placed in three or more standardised categories with no category above ~40%. Candidates for cross-listing or renaming.
  • Label candidates per cluster with wording frequency.
  • For closed sorts: per-card placement distribution and the share placed in the intended category.

Tree test

Per task, over participants:

  • Success = reached a correct destination (last click) / participants.
  • Directness = reached the destination without backing up / participants.
  • Time = median seconds to the final click.
  • First click = distribution of the first top-level choice; the correct first click strongly predicts success.
  • Wrong destinations = where unsuccessful participants ended; group by branch.

Interpretation:

SuccessDirectnessReading
highhighStructure and labels work
highlowFound eventually; a sibling label competes or the path is long
lowhighConfident wrong path: a label misleads
lowlowStructure problem: no obvious home

Conventional thresholds: success below ~60% or directness below ~50% needs action; between 60-80% success, look at the wrong-path branches before deciding.

First-click test

  • Correct first click rate per task; below ~75% the cue on the page is weak.
  • Click map: where wrong clicks landed, to tell a label problem from a layout problem.

Comparing two structures

Same tasks, participants split between trees. Compare per-task success and directness; a difference under the sampling noise of ~50 participants per arm (roughly 10-15 points) is not decisive on its own.

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