Closing the Findability Gap: 8 better practices from information architecture

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  • You bet; email me at lou@louisrosenfeld.com That said, I'll send you a PDF rather than a PPT...
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  • Hi Lou,

    Another great presentation.

    Is it possible to obtain a PPT copy of this document?

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  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
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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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