Your SlideShare is downloading. ×
8 better practices from information architecture By: Lou Rosenfeld
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

8 better practices from information architecture By: Lou Rosenfeld

771

Published on

Published in: Design, Education, Technology
0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
771
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
37
Comments
0
Likes
4
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • http://xkcd.com/773/
  • http://www.semanticreview.com/images/semantic-data.jpg
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net
  • Funnel: http://www.orionweb.net/wp-content/uploads/conversion-funnel.png Sitemap: http://www.peacockvaughninsurance.com/images/SiteMap.bmp
  • Onion courtesy Eva-Lotta Lamm
  • Transcript

    • 1. 8 better practices from information architecture Lou Rosenfeld
    • 2. Hello, my name is Louwww.louisrosenfeld.com | www.rosenfeldmedia.com 2
    • 3. 3
    • 4. The state ofcontemporary findability 3
    • 5. 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? 4
    • 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. Information architecture:8 better practices for findability1. Diagnose the important problems2. Balance your evidence3. Advocate for the long term4. Measure engagement5. Support contextual navigation6. Improve search across silos7. Combine design approaches effectively8. Tune your design over time 7
    • 15. #1Diagnose theimportant problems 8
    • 16. A 9
    • 17. A Not all queries are distributed equally 9
    • 18. A Nor do they diminish gradually 9
    • 19. A 80/20 rule isn’t quite accurate 9
    • 20. ( 10
    • 21. ( 10
    • 22. ( 10
    • 23. ( 10
    • 24. The Long Tail is( much longer than you’d suspect 10
    • 25. Zipf Distribution in text 11
    • 26. It’s Zipf’s World;we just live in it A little... • queries • tasks • ways to navigate • features • documents ...goes a long way 12
    • 27. UNVERIFIED RUMOR: 90% of Microsoft.com contenthas never been accessed... not even once TAKEAWAY: FOCUS ON THE STUFFTHAT MATTERS!
    • 28. Continually prioritizeto dowhat’s important... 14
    • 29. ...and continually fix (withinto doan IA report card) 15
    • 30. #2Balance your evidence 16
    • 31. from Christian Rohrer: http://is.gd/95HSQ2 17
    • 32. Balanced research leads to true insight, new opportunitiesfrom Christian Rohrer: http://is.gd/95HSQ2 17
    • 33. 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) 18
    • 34. Balance over time:From projects to processes Example: the rolling content inventory 19
    • 35. Develop a research regimento do balanced by time, quadrant Each week, for example... • Analyze analytics for trends (Behavioral + Quantitative) • Task analysis of common needs (Behavioral + Qualitative) Each month... • User survey (Attitudinal + Quantitative) • Exploratory analysis of analytics data (Behavioral + Qualitative) Each quarter... • Field study (Behavioral/Attitudinal + Qualitative) • Card sorting (Attitudinal + Qualitative/Quantitative) 20
    • 36. #3Advocate for the long-term 21
    • 37. S Typical design focus Stuff that gets ignored: mission, vision, charter, goals, KPI, objectives 22
    • 38. For starters, develop yourto doproject’s elevator pitch Read Gamestorming (Gray, Brown, Macanufo); O’Reilly, 2010). http://amzn.to/nnpERG 23
    • 39. #4Measure engagement 24
    • 40. Measuringconversions?No problem... 25
    • 41. ..measuringanything else?Good luck!
    • 42. 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... 26
    • 43. Use gradual engagement to do model to isolate, measure tasks Example: adoption of features; can you measure movement between layers? Layer 0: User visits the site (unauthenticated; no cookies, no nothing) Layer 1: User asks the site a question (for example, a search query) Layer 2: Site asks the user a question (would you like save this product to a wish list?) Layer 3: Site suggests something to the user (you might enjoy these products ordered by people like you) Layer 4: Site acts on the users behalf (weve gone ahead and saved these products to yourMore on gradual engagement: accounts list of frequently-ordered items)http://bit.ly/9hPqyx 27
    • 44. #5Support contextual navigation 28
    • 45. Contextual navigation: your site’s desire lines Determinethrough content modeling, sitesearch analytics Deep navigation requires content modeling : a better approach to deep IA and content structuring
    • 46. 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 30
    • 47. Important metadata attributes emergefrom content modeling Metadata that matters most 31
    • 48. Make content modeling ato doparticipatory design exercise
    • 49. Make content modeling ato doparticipatory design exercise•Provide subjects with “de-oriented” samples ofcontent types... and common tasks•Have them draw “desire lines” and startingpoints, and identify gaps in content types•Learn from “think out loud” and by identifyingcommon patterns•More info: Atherton et al.’s “domain modeling”presentation: http://slidesha.re/fzChQB
    • 50. #6Improve search across silos 33
    • 51. Reconsidering the search UI... 34
    • 52. ...by contextualizing “advanced”features, focusing on revision
    • 53. ...by contextualizing “advanced”features, focusing on revision search session patterns 1. solar energy 2. how solar energy works
    • 54. ...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
    • 55. ...by contextualizing “advanced”features, focusing on revision 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
    • 56. ...by contextualizing “advanced”features, focusing on revision 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
    • 57. ...by contextualizing “advanced”features, focusing on revision 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
    • 58. Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s) 36
    • 59. Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s)search pattern:TA292761 36
    • 60. Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s) search pattern: regulations March 2011search pattern:TA292761 36
    • 61. Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s) search pattern: regulations March 2011 search pattern: regulations Owenssearch pattern:TA292761 36
    • 62. Recognizingspecialized queries(e.g., proper nouns,dates, unique ID#s) search pattern: regulations March 2011 search pattern: regulations Owens search pattern:search pattern: regulationsTA292761 Caterpillar 36
    • 63. ...and designing specialized search result 37
    • 64. ...and designing specialized search result 37
    • 65. ...and designing specialized search result 37
    • 66. Poor search results returned by search engineContent objectsfrom productcontent model...and designing specialized search result 37
    • 67. Read a book chapter onto dosession analysisYou’ll find one in my bookSearch Analytics for Your Sitehttp://bit.ly/quFxdz 38
    • 68. #7Combine design approacheseffectively 39
    • 69. Y 40
    • 70. Y Narrow, deep content access 40
    • 71. V 41
    • 72. V ...to editorially rich content 41
    • 73. 42
    • 74. Manuallyselected results 42
    • 75. Manuallyselected results ...complement raw results 42
    • 76. Treat your content to do like an onion 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) refresh monthly (e.g., UserTesting.com) tagged by experts “traditional” lab-based titled according to 3 (topical tags) user testing guidelines content models for A/B testing structured according 4 contextual navigation to schema 43
    • 77. Treat your content to do like an onion Each layer is cumulative; most important content is informationlayer usat thecore 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) refresh monthly (e.g., UserTesting.com) tagged by experts “traditional” lab-based titled according to 3 (topical tags) user testing guidelines content models for A/B testing structured according 4 contextual navigation to schema 43
    • 78. #8Tune your design over time 44
    • 79. Your site is a moving targetbuilt on moving targets 45
    • 80. I 46
    • 81. I Time to Interest in the study! football team: going ...going gone 46
    • 82. I 47
    • 83. Before Tax DayI 47
    • 84. I 48
    • 85. After Tax DayI 48
    • 86. Move from time-boxedto doprojects to ongoing processes Example: the rolling content inventory 49
    • 87. Summary:8 IA better practices1. Diagnose the important problems2. Balance your evidence3. Advocate for the long term4. Measure engagement5. Support contextual navigation6. Improve search across silos7. Combine design approaches effectively8. Tune your design over time 50
    • 88. S Let’s stop boiling the ocean 50
    • 89. Say hello Lou Rosenfeld lou@louisrosenfeld.com Rosenfeld Media www.louisrosenfeld.com | @louisrosenfeld www.rosenfeldmedia.com | @rosenfeldmedia 51

    ×