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Design to Refine: Developing a tunable information architecture

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My UX London workshop; short version of the full-day workshop I'm teaching this year in San Francisco, Atlanta, and Chicago: http://bit.ly/gL7HaH

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Design to Refine: Developing a tunable information architecture

  1. 1. Design to RefineDeveloping a tunable information architectureLou Rosenfeld •  Rosenfeld Media •  rosenfeldmedia.com London •  14 April 2011
  2. 2. Hello, my name is Lou
  3. 3. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  4. 4. I’ve already dissed redesignSee the slides here:http://www.slideshare.net/lrosenfeld/
  5. 5. The alternatives to redesign1. Prioritize: Identify the important problems regularly2. Tune: Address those problems regularly3. Be opportunistic: Look for low-hanging fruit
  6. 6. Prioritize becausea little goes a long way
  7. 7. A handful of your queries/ways to navigate/documents meet A little data goes a long waythe needs of the few audiences that use your site most
  8. 8. A handful of your queries/ways to navigate/documents meet A little data goes a long waythe needs of the few audiences that use your site most LOVE IT
  9. 9. A handful of your queries/ways to navigate/documents meet A little data goes a long waythe needs of the few audiences that use your site most LOVE IT LEAVE IT
  10. 10. Zipf in text
  11. 11. Report card for essential wants and needs
  12. 12. Be an incrementalist:tune because things change
  13. 13. From projects to processes:a regular regimen of design Example: the rolling content inventory
  14. 14. Impact of change on design(queries)
  15. 15. Be an opportunist:look for the low-hanging fruit1. Top-down navigation: Anticipates interests/questions at arrival2. Bottom-up (contextual) navigation: Enables answers to emerge3. Search: Handles specific information needs
  16. 16. Life by a thousand cuts 50% of users are search dominantx 5% of all queries are typos, fixed by spell checking. 2.5% improvement to the UX 50% of all users are search dominantx 30% (best bet results for top 100 queries) 15% improvement to the UXDitto for improving content, search results design,navigation design…
  17. 17. Summary You can refine 1. Prioritize the problems that are most important to your users 2. Regularly address these problems 3. Identify opportunities to make small improvements that go a long way
  18. 18. Prioritizing and TuningTop-Down Navigation
  19. 19. The data-driven main page:Who wants what and when?
  20. 20. Who wants what?US English speakers
  21. 21. Who wants what?German speakers
  22. 22. When do they want it?
  23. 23. Commerce sites get it
  24. 24. The IRS gets it
  25. 25. But really, who caresabout the main page?
  26. 26. But really, who caresabout the main page?
  27. 27. The risk of main page fixationFrom Tony Dunn’s Tales from Redesignland(http://redesignland.blogspot.com/)
  28. 28. Focusing on main page =taking Zipf too far...plus lots of competition (Google, ads/landing pages)
  29. 29. The tail that wags the dog:site map drivesimproved site hierarchy
  30. 30. Site map by tool, unit, and format
  31. 31. Site map by tool, unit, and format
  32. 32. Site map by tool, unit, and format
  33. 33. User-centered site mapUser-centered site map...
  34. 34. Asking the possiblefrom your site index
  35. 35. Specialized site indices
  36. 36. Specialized site indices
  37. 37. Specialized site indices Cisco’s site indices are specialized by content type (products, services)
  38. 38. Best bet-based site indices MSU’s site index is built on popular information needs (based on best bet search results)
  39. 39. Going broad and deep withguides (AKA microsites)
  40. 40. Vanguard’s main page lovesguides
  41. 41. Vanguard’s main page lovesguides
  42. 42. The Tax Center is a guide
  43. 43. One more example: IRS
  44. 44. One more example: IRS
  45. 45. ...e-filing is presented assequential steps
  46. 46. Summary: Top-down navigation Prioritize main page content and layout 1. Confuse as necessary by diverting attention 2. Counter politics with data; e.g., use seasonality to drive design Tune and prioritize site-wide navigation 3. Use the site map as a skunkworks for site-wide hierarchy 4. Base site indices on specialized content or popular information needs (e.g., best bets) 5. Use guides (micro-sites) as narrow/deep complement to broad/shallow navigation schemes
  47. 47. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  48. 48. concert calendar album pages artist descriptions TV listings Demonstration: Content Modelingalbum reviews discography artist bios
  49. 49. What are the common content objects in your site? album pages artist bios artist descriptions album reviews 53
  50. 50. How do they fit together? concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios
  51. 51. What content objects are missing? concert calendar And how do they fit? album pages artist descriptions TV listingsalbum reviews discography artist bios
  52. 52. Where do you start? concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios
  53. 53. How will you connect those objects?
  54. 54. Use content modelsfor content that’s... Homogeneous High-volume High importance What’s the most important deep content in your site?
  55. 55. Use content modelswhen you need to... Incorporate user research into your deep content Improve contextual navigation Identify missing content Prioritize metadata choices Really benefit from your CMS
  56. 56. Steps for developingcontent models1. Determine key audiences (who’s using it?)2. Select important tasks to test (what are they using it for?)3. Determine important content areas (what do they want?)4. Determine content types (what are they using?)5. Determine metadata attributes (how will we connect the objects?)6. Determine contextual linking rules (where should the objects lead us to next?)
  57. 57. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  58. 58. Prioritizing and TuningContextual Navigation
  59. 59. Establishing Desire LinesUse Content modeling • Site search analytics
  60. 60. Where do searches begin?Not just the mainpage, according to aUser InterfaceEngineering study(http://is.gd/j1NHeS)
  61. 61. Using site search analyticsto identify desire lines
  62. 62. Choose acommon contenttype (e.g., events) !Where should !users go from here? !
  63. 63. ! ! ! ! ! !Analyze frequent queries generated from each content sample
  64. 64. ! ! !Can you type these queries to improve yourcontent model?Link events to:• the site’s articles on the event’s topic• info on locales for each event
  65. 65. What content typesshould we be connecting?
  66. 66. Important content types emerge from content modeling concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios
  67. 67. Using SSA to prioritize contenttypes
  68. 68. Getting content types out ofsite search analytics Take an hour to... • Analyze top 50 queries (20% of all search activity) • Ask and iterate: “what kind of content would users be looking for when they searched these terms?” • Add cumulative percentages Result: prioritized list of potential content types #1) application: 11.77% #2) reference: 10.5% #3) instructions: 8.6% #4) main/navigation pages: 5.91% #5) contact info: 5.79% #6) news/announcements: 4.27%
  69. 69. What should we use toconnect content types?
  70. 70. Which metadata attributes will yourcontent model depend upon?
  71. 71. More on prioritizing metadata attributes
  72. 72. Prioritizing semantic relationships
  73. 73. How do weprioritize content?
  74. 74. Some content value variables I
  75. 75. Some content value variables I UsabilityPopularityCredibility
  76. 76. Some content value variables Currency Freshness Authority Follows guidelines (e.g., titling, I metadata) UsabilityPopularityCredibility
  77. 77. Some content value variables Currency Freshness Authority Follows guidelines (e.g., titling, I metadata) UsabilityPopularityCredibility Strategic value Addresses compliance issues (e.g., Sarbanes/Oxley) Content owners are good partners
  78. 78. Subjectively “grade” your content’s value1.Choose appropriatevalue criteria for eachcontent area2.Weight criteria (total= 100%)3.Subjectively grade foreach criterion4.weight x grade =score5.Add scores foroverall score
  79. 79. Subjectively “grade” your content’s value Subjective assessment1.Choose appropriatevalue criteria for eachcontent area2.Weight criteria (total= 100%)3.Subjectively grade foreach criterion4.weight x grade =score5.Add scores foroverall score
  80. 80. Put the grades together for a moreobjective “report card” Helps prioritize content migrations, refreshes, ...
  81. 81. Put the grades together for a moreobjective “report card” Objectifies subjective assessments Helps prioritize content migrations, refreshes, ...
  82. 82. Summary:contextual navigation Use content modeling and site search analytics to 1. Identify and prioritize content types 2. Identify desire lines 3. Improve contextual navigation between content types 4. Identify and prioritize metadata attributes Prioritize content areas/subsites by establishing balanced value criteria
  83. 83. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  84. 84. Group exercise:Site search analytics
  85. 85. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  86. 86. Prioritizing and Tuning Search
  87. 87. Make “the Box” accommodatemost searchers’ queries
  88. 88. How long are our queries? Top 500 queries (37% of all traffic)
  89. 89. Mean = 10.6 charactersMedian = 10 characters
  90. 90. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longer
  91. 91. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20s !
  92. 92. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20sDesired: @30 characters;Can you get that many? !
  93. 93. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20sDesired: @30 characters;Can you get that many? !Safe: @15-20 characters
  94. 94. We’ve seen this before:auto-completing queries
  95. 95. Auto-completing from aknown, common items (e.g.,
  96. 96. Auto-completing from aknown, common items (e.g., Uses known terms: e.g., movie titles and actor/director names
  97. 97. Auto-completing from queries
  98. 98. Uses common queriesAuto-completing from queries
  99. 99. Auto-completing from bestbets
  100. 100. Auto-completing from bestbets Uses best bets
  101. 101. Making change easy:supporting query refinement
  102. 102. The absolutemeaninglessness ofadvanced search
  103. 103. The absolute meaninglessness of advanced search !At University of Alaska-Fairbanks,advanced = expanded search
  104. 104. The absolute meaninglessness of advanced search !At University of Alaska-Fairbanks,advanced = expanded search At the IRS, advanced = narrowed search !
  105. 105. Contextualizing “advanced” features
  106. 106. Look to session data forprogression and context
  107. 107. Look to session data forprogression and context search session patterns 1. solar energy 2. how solar energy works
  108. 108. Look to session data forprogression and context search session patterns 1. solar energy 2. how solar energy works search session patterns 1. solar energy 2. energy
  109. 109. Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns 1. solar energy 2. energy
  110. 110. Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns search session patterns 1. solar energy 1. solar energy 2. explain solar energy 2. energy
  111. 111. Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns search session patterns 1. solar energy 1. solar energy 2. explain solar energy 2. energy search session patterns 1. solar energy 2. solar energy news
  112. 112. Improving performance forspecialized queries
  113. 113. Recognizing proper nouns,dates, and unique ID#s
  114. 114. Surfacingspecialized content typesin search results
  115. 115. Tuning Search Results:Handling specialized answers
  116. 116. Tuning Search Results:Handling specialized answers
  117. 117. Tuning Search Results:Handling specialized answers
  118. 118. Tuning Search Results: Handling specialized answers“Product quick links” come directly from product content modelThese results are a strong counterbalance to raw results
  119. 119. When raw isn’t good enough:best bet search results
  120. 120. best bet #1
  121. 121. best bet #1best bet #2
  122. 122. best bet #1best bet #2even more best bets
  123. 123. best bet #1best bet #2even more best betsraw results
  124. 124. best bet #1best bet #2even more best betsraw results
  125. 125. best bet #1 best bet #2 even more best betscompetition raw results
  126. 126. best bet #1 best bet #2 even more best betscompetition danger? raw results
  127. 127. best bet #1 best bet #2 even more best betscompetition danger? data raw results
  128. 128. The 0 search results page:search’s equivalent of the 404
  129. 129. Tuning Search Results: 0 results pagesNot helpful
  130. 130. Tuning Search Results: 0 results pagesNot helpfulMuch better: “Did youmean?” and Popular Searches
  131. 131. Summary: Search systems Tune query entry 1. Make “The Box” wide enough 2. Support query auto-completion to focus queries 3. Surface the right features to support query refinement 4. Recognize and take advantage of specialized queries Tune search results design 5. Surface specialized content types as results for specialized queries 6. Complement raw results with best bets 7. Enable recovery from finding 0 search results
  132. 132. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  133. 133. Changing your workand your organization
  134. 134. Doing your work differently1. Processes, not projects2. Rebalancing your research and design
  135. 135. From time-boxed projectsto ongoing processes Example: the rolling content inventory
  136. 136. What else can roll?Most everything Each week, for example... • Content scouting and sampling (rather than inventory) • Analyze analytics to identify spikes, new trends Each month... • Identify new tasks, run new task analysis studies • Develop new best bet search results Each quarter... • Field study • Review and tune personas
  137. 137. Build a practice that’sbalanced and data-driven
  138. 138. User Research Landscapefrom Christian Rohrer: http://is.gd/95HSQ2
  139. 139. User Research Landscape Ongoing coverage of each of these 4 quadrantsfrom Christian Rohrer: http://is.gd/95HSQ2
  140. 140. Lou’s TABLE OFOVERGENERALIZED Web Analytics User Experience DICHOTOMIES Users intentions and What they Users behaviors (whats motives (why those things analyze happening) happen) Qualitative methods for What methods Quantitative methods to explaining why things they employ determine whats happening happen Helps users achieve goals What theyre Helps the organization meet (expressed as tasks ortrying to achieve goals (expressed as KPI) topics of interest) Uncover patterns and How they use Measure performance (goal- surprises (emergent data driven analysis) analysis) Statistical data ("real" data Descriptive data (in smallWhat kind of data in large volumes, full of volumes, generated in lab they use errors) environment, full of errors)
  141. 141. Getting your organizationto support your work1. Making friends and allies2. Changing your leaders’ minds
  142. 142. Making friends and allies
  143. 143. Showing content ownershow their content performs
  144. 144. Showing content ownershow their content performs
  145. 145. Helping marketingdevelop better messagingJargon vs. Plain Language at Washtenaw Community College • Online courses were marketed using terms “College on Demand” (“COD”) and “FlexEd”; signup rates were poor • Compare jargon with “online” (used in 213 other queries) • Content was retitled rather than re-marketed
  146. 146. Helping IT say “no” with authorityReduce pressure to solve problems with technologies by making what we have workMinimize radical changes to platforms • Enterprise search • Content management systems • Analytics applications • ...
  147. 147. Changing leaders’ minds
  148. 148. Talking pointsfor refining, against redesigning 1. Solve the problem(s) 2. Save money 3. Reduce/end radical organizational changes
  149. 149. Solving the problem(s)• Forcing the issue: ban the term “redesign” from discussions• Data-driven definition / prioritization / tuning / opportunism• Creating anchors to keep project from spinning out of control: elevator pitch / mission / vision / goals / KPI
  150. 150. This can be very, very helpful Gamestorming by Dave Gray, Sunni Brown, and James Macanufo (O’Reilly, 2010)
  151. 151. Saving money• Life by a thousand cuts: small changes have huge impacts (see: Zipf)• Reuse and retain technology investments• Retain institutional knowledge• Get more from your (empowered) team and make it pay for itself• Spend less on external support and fire your agency
  152. 152. Reduce/end radicalorganizational changes• End the pendulum swing from centralized to decentralized approaches• Reorganize information, not people• Build self-sustaining, steady in-house capabilities to prioritize and tune
  153. 153. Being prepared to fail
  154. 154. Sometimes your leadersare in a hurry
  155. 155. Sometimes your leadersare not very smart
  156. 156. Sometimes your organizationis immature
  157. 157. Nurit Peres’ Company UX Maturity Model(http://is.gd/x1dOuP)
  158. 158. Renato Feijó’s UX Maturity Model(http://is.gd/dul2t2)
  159. 159. Always be ready to gounder the radar
  160. 160. Summary: changing your workand your organization Do your work differently 1. Move from time-based projects to ongoing processes 2. Build a balanced, data-driven practice Get your organization to support your work 3. Make friends and allies 4. Change leaders’ minds by • Solving problems • Saving money • Reducing radical change Be prepared to fail
  161. 161. Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization
  162. 162. Say hello Lou Rosenfeld lou@louisrosenfeld.com Rosenfeld Media  www.louisrosenfeld.com | @louisrosenfeld www.rosenfeldmedia.com | @rosenfeldmedia

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