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Closing theFindability Gap8 better practices frominformation architectureLou Rosenfeld •  Rosenfeld Media •  rosenfeldmedi...
Hello, my name is Lou www.louisrosenfeld.com | www.rosenfeldmedia.com
The state ofcontemporary findability
Some questions that youprobably can’t answer• Who are your content’s primary audiences?• What are the five major tasks and ...
Why can’t we getfindability right?
Why can’t we getfindability right?
Why can’t we getfindability right?• We don’t know how to diagnose
Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure
Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations
Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations• Ill-...
Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations• Ill-...
Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations• Ill-...
Data is binaryInformation isn’t
Data is binaryInformation isn’t
Information architecture:8 better practices for findability 1. Diagnosing the important problems 2. Balancing our evidence ...
#1Diagnosing theimportant problems
A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most import...
A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most import...
A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most import...
A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most import...
A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most import...
A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most import...
(and the tail is quite long)
(and the tail is quite long)
(and the tail is quite long)
(and the tail is quite long)
(and the tail is quite long)
The Long Tail is(and the tail is quite long) much longer than you’d ...
Zipf Distribution in text
It’s Zipf’s World;we just live in it A little... • queries • tasks • ways to navigate • features • document...
UNVERIFIED RUMOR:
UNVERIFIED RUMOR: 90% of
UNVERIFIED RUMOR: 90% ofMicrosoft.com content
UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed...
UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once
UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY:
UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCU...
UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCU...
UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCU...
#2Balancing our evidence
from Christian Rohrer: http://is.gd/95HSQ2
Balanced research leads to true insight, ...
Lou’s TABLE OFOVERGENERALIZED Web Analytics User Experience DICHOTOMIES ...
#3Advocating for the long-term
Steward Brand’s Pace Layeringmodel Typical design focus Stuff that ...
#4Measuring engagement
Measuringconversions?No problem...
..measuringanything else? Good luck!
The missing metricsof in-betweenness• Orientation (“What can I do here?”)• Engagement (“I like this; do you?”)• Connection...
#5Supportingcontextual navigation
Contextual navigation:your site’s desire lines
Contextual navigation: your site’s desire lines Determinethrough content modeling, site search analytics
Contextual navigation: your site’s desire lines Determinethrough content modeling, site search analytics ...
Important content objects emerge concert calendar from content modeling (example:...
Important content objects emerge concert calendar from content modeling (exam...
Important metadata attributes emergefrom content modeling
Important metadata attributes emergefrom content modeling Metadata that ...
#6Improving search across silos
Reconsidering the search UI...
...by contextualizing “advanced”features, focusing on revision
...by contextualizing “advanced”features, focusing on revision search session patterns 1. solar energy 2. how solar energy...
...by contextualizing “advanced”features, focusing on revision search session patterns 1. solar energy 2. how solar ene...
...by contextualizing “advanced”features, focusing on revisionsearch session patterns search session patterns 1. sola...
...by contextualizing “advanced”features, focusing on revision search session patterns search session patterns ...
...by contextualizing “advanced”features, focusing on revision search session patterns search session patterns ...
Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s)
...and designing specialized search results
...and designing specialized search results
...and designing specialized search results
Content objects from productcontent model...and designing specialized search results
Poor search results returned by search engineContent objec...
#7Combining design approacheseffectively
Yes, manual effort is still asimportant as tools
Yes, manual effort is still asimportant as tools Narrow, deep content access
Vanguard’s Tax Center is asimple, low-tech, editorial
Vanguard’s Tax Center is asimple, low-tech, editorial ...to editorially rich content
Manuallyselected results
Manuallyselected results ...complement raw results
Treat your content Each layer is ...
#8Tuning designs over time
Your site is a moving targetbuilt on moving targets
Impact of change on design(queries)
Impact of change on design(queries) Interest in the football team: going...
Impact of change on design(queries) Interest in the football team: going... ...going...
Impact of change on design(queries) Interest in the football team: going... ...going... ...
Impact of change on design(queries) Time to Interest in the ...
IRS before Tax Day
Before Tax DayIRS before Tax Day
IRS after Tax Day
After Tax DayIRS after Tax Day
Summary:8 IA better practices1. Diagnosing the important problems2. Balancing our evidence3. Advocating for the long term4...
Summary:8 IA better practices1. Diagnosing the important problems2. Balancing our evidence3. Advocating for the long term4...
Say hello Lou Rosenfeld lou@louisrosenfeld.com Rosenfeld Media  www.louisrosenfeld.com | @louisrosenfeld www.rosenfeldmedi...
Closing the Findability Gap: 8 better practices from information architecture
Closing the Findability Gap: 8 better practices from information architecture
Closing the Findability Gap: 8 better practices from information architecture
Closing the Findability Gap: 8 better practices from information architecture
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Closing the Findability Gap: 8 better practices from information architecture

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Closing the Findability Gap: 8 better practices from information architecture

  1. Closing theFindability Gap8 better practices frominformation architectureLou Rosenfeld •  Rosenfeld Media •  rosenfeldmedia.com
  2. Hello, my name is Lou www.louisrosenfeld.com | www.rosenfeldmedia.com
  3. The state ofcontemporary findability
  4. Some questions that youprobably can’t answer• Who are your content’s primary audiences?• What are the five major tasks and needs each has?• Are you satisfying those tasks and needs?• What data support your thinking?• How do you measure success?
  5. Why can’t we getfindability right?
  6. Why can’t we getfindability right?
  7. Why can’t we getfindability right?• We don’t know how to diagnose
  8. Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure
  9. Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations
  10. Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations• Ill-equipped decision-makers
  11. Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations• Ill-equipped decision-makers• Short-term thinking
  12. Why can’t we getfindability right?• We don’t know how to diagnose• We don’t know how to measure• Siloed organizations• Ill-equipped decision-makers• Short-term thinking• Semantic illiteracy
  13. Data is binaryInformation isn’t
  14. Data is binaryInformation isn’t
  15. Information architecture:8 better practices for findability 1. Diagnosing the important problems 2. Balancing our evidence 3. Advocating for the long term 4. Measuring engagement 5. Supporting contextual navigation 6. Improving search across silos 7. Combining design approaches effectively 8. Tuning our designs over time
  16. #1Diagnosing theimportant problems
  17. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
  18. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences Not all queries are distributed equally
  19. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
  20. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences Nor do they diminish gradually
  21. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
  22. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences 80/20 rule isn’t quite accurate
  23. (and the tail is quite long)
  24. (and the tail is quite long)
  25. (and the tail is quite long)
  26. (and the tail is quite long)
  27. (and the tail is quite long)
  28. The Long Tail is(and the tail is quite long) much longer than you’d suspect
  29. Zipf Distribution in text
  30. It’s Zipf’s World;we just live in it A little... • queries • tasks • ways to navigate • features • documents ...goes a long way
  31. UNVERIFIED RUMOR:
  32. UNVERIFIED RUMOR: 90% of
  33. UNVERIFIED RUMOR: 90% ofMicrosoft.com content
  34. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed...
  35. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once
  36. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY:
  37. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCUS ON
  38. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCUS ON THE STUFF
  39. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCUS ON THE STUFFTHAT MATTERS!
  40. #2Balancing our evidence
  41. from Christian Rohrer: http://is.gd/95HSQ2
  42. Balanced research leads to true insight, new opportunitiesfrom Christian Rohrer: http://is.gd/95HSQ2
  43. 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)
  44. #3Advocating for the long-term
  45. Steward Brand’s Pace Layeringmodel Typical design focus Stuff that gets ignored: mission, vision, charter, goals, KPI, objectives
  46. #4Measuring engagement
  47. Measuringconversions?No problem...
  48. ..measuringanything else? Good luck!
  49. The missing metricsof in-betweenness• Orientation (“What can I do here?”)• Engagement (“I like this; do you?”)• Connection/cross-promotion (“What goes with this?”)• Authority (“I trust this”)• and many more...
  50. #5Supportingcontextual navigation
  51. Contextual navigation:your site’s desire lines
  52. Contextual navigation: your site’s desire lines Determinethrough content modeling, site search analytics
  53. Contextual navigation: your site’s desire lines Determinethrough content modeling, site search analytics Deep navigation requires content modeling: a better approach to deep IA and content structuring
  54. Important content objects emerge concert calendar from content modeling (example: BBC) album pages artist descriptions TV listingsalbum reviews discography artist bios
  55. Important content objects emerge concert calendar from content modeling (example: BBC) album pages artist descriptions TV listings Content that matters mostalbum reviews discography artist bios
  56. Important metadata attributes emergefrom content modeling
  57. Important metadata attributes emergefrom content modeling Metadata that matters most
  58. #6Improving search across silos
  59. Reconsidering the search UI...
  60. ...by contextualizing “advanced”features, focusing on revision
  61. ...by contextualizing “advanced”features, focusing on revision search session patterns 1. solar energy 2. how solar energy works
  62. ...by contextualizing “advanced”features, focusing on revision search session patterns 1. solar energy 2. how solar energy works search session patterns 1. solar energy 2. energy
  63. ...by contextualizing “advanced”features, focusing on revisionsearch 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
  64. ...by contextualizing “advanced”features, focusing on revision 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
  65. ...by contextualizing “advanced”features, focusing on revision 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
  66. Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s)
  67. ...and designing specialized search results
  68. ...and designing specialized search results
  69. ...and designing specialized search results
  70. Content objects from productcontent model...and designing specialized search results
  71. Poor search results returned by search engineContent objects from productcontent model...and designing specialized search results
  72. #7Combining design approacheseffectively
  73. Yes, manual effort is still asimportant as tools
  74. Yes, manual effort is still asimportant as tools Narrow, deep content access
  75. Vanguard’s Tax Center is asimple, low-tech, editorial
  76. Vanguard’s Tax Center is asimple, low-tech, editorial ...to editorially rich content
  77. Manuallyselected results
  78. Manuallyselected results ...complement raw results
  79. Treat your content Each layer is cumulative; most important like an onion content is at the core informationlayer usability content strategy architecture indexed by search 0 engine leave it alone leave it alone squeaky wheel issues 1 tagged by users addressed refresh annually tagged by experts (non- test with a service 2 topical tags) (e.g., UserTesting.com) refresh monthly tagged by experts “traditional” lab-based titled according to 3 (topical tags) user testing guidelines content models for structured according 4 contextual navigation A/B testing to schema
  80. #8Tuning designs over time
  81. Your site is a moving targetbuilt on moving targets
  82. Impact of change on design(queries)
  83. Impact of change on design(queries) Interest in the football team: going...
  84. Impact of change on design(queries) Interest in the football team: going... ...going...
  85. Impact of change on design(queries) Interest in the football team: going... ...going... gone
  86. Impact of change on design(queries) Time to Interest in the study! football team: going... ...going... gone
  87. IRS before Tax Day
  88. Before Tax DayIRS before Tax Day
  89. IRS after Tax Day
  90. After Tax DayIRS after Tax Day
  91. Summary:8 IA better practices1. Diagnosing the important problems2. Balancing our evidence3. Advocating for the long term4. Measuring engagement5. Supporting contextual navigation6. Improving search across silos7. Combining design approaches effectively8. Tuning our designs over time
  92. Summary:8 IA better practices1. Diagnosing the important problems2. Balancing our evidence3. Advocating for the long term4. Measuring engagement5. Supporting contextual navigation6. Improving search across silos7. Combining design approaches effectively8. Tuning our designs over time Let’s stop boiling the ocean
  93. Say hello Lou Rosenfeld lou@louisrosenfeld.com Rosenfeld Media  www.louisrosenfeld.com | @louisrosenfeld www.rosenfeldmedia.com | @rosenfeldmedia

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