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Card Sorting- Information Architecture Technique

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How to conduct a Card Sort to address Information Architecture problems with Find-ability

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Card Sorting- Information Architecture Technique

  1. 1. Information Architecture Technique Card Sorting
  2. 2. Why use Card Sorting Method for Addressing Problems of Find-ability
  3. 3. 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
  4. 4. What is Information Architecture?
  5. 5. 5 Planes of User Experience Skeleton Scope Strategy Surface 1 2 3 Structure
  6. 6. Skeleton Scope Strategy Surface 1 2 3 Structure 5 Planes of User Experience Information Architecture
  7. 7. Card Sorting Overview
  8. 8. • 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
  9. 9. Each ‘Card’ consists of: • Name • Description • Fit Confidence
 Perfect, Good, Fair • Importance (optional)
 Very Important - Not Important Card Sorting Overview
  10. 10. Two Primary Methods Open Card Sort vs Closed Card Sort
  11. 11. 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.
  12. 12. Open Card Sort Method
  13. 13. 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
  14. 14. 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
  15. 15. Open Card Sort Analysis
  16. 16. Shows how often an item was grouped with another item, factoring quality of fit. Analysis - Similarity Matrix / Contour Map
  17. 17. 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. Analysis - Similarity Matrix / Contour Map
  18. 18. How to construct using Excel: • 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. Analysis - Similarity Matrix / Contour Map
  19. 19. 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
  20. 20. 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. Analysis - Dendrogram based on Cluster Analysis
  21. 21. Example of 5 Groups,
 Based on height. Analysis - Dendrogram based on Cluster Analysis
  22. 22. Example of 3 Groups,
 Based on height. Analysis - Dendrogram based on Cluster Analysis
  23. 23. Example of 10 Groups,
 Based on height. Analysis - Dendrogram based on Cluster Analysis
  24. 24. How to construct using Past
 (or other statistics software): • Use the data from the Similarity Matrix • Multivariate -> Clustering -> Classical Analysis - Dendrogram based on Cluster Analysis 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/
  25. 25. Closed Card Sort Methods
  26. 26. 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
  27. 27. 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
  28. 28. Closed Card Sort Method 2 - Analysis
  29. 29. Shows the percentage of participants that grouped an item into a particular category. Analysis - Correlation Table
  30. 30. How to construct using Excel: • 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 Analysis - Similarity Matrix / Contour Map
  31. 31. 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)
  32. 32. Results
  33. 33. Show how items were placed between the initial proposal and the result of the Close Card Sort. Results
  34. 34. Summary
  35. 35. • 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

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