Summary of a few selected topics (social IA, data-driven IA and Documenting IA) at the http://www.iasummit.org/2007/

1. IA Summit 2007
trip report
David Karemaker
& Jacco Nieuwland
User Intelligence
May 16nd, 2007
21 May 2007 (c) 2007, User Intelligence 1

2. 21 May 2007 (c) 2007, User Intelligence 2

3. IA summit
The 8th IA Summit
•
• Theme: ‘Enriching IA’
Jacco’s 3rd, David’s 1st
•
• 570 attendees
• 2 days of pre-conference workshops
• 3 days of conference sessions
21 May 2007 (c) 2007, User Intelligence 3

4. What will we bring you?
• Pre-conference workshop: Social IA
• Session reports are limited: focus on two
main themes
• Data driven IA
• Documenting rich IA
21 May 2007 (c) 2007, User Intelligence 4

5. Preconference workshop
Social Information Architecture Workshop
Gene Smith, Rashmi Sinha (slideshare), Thomas Vander Wal
• Three separate, slightly interactive
presentations
• About 20 attendees
21 May 2007 (c) 2007, User Intelligence 5

6. PCW – Social IA – Gene Smith
Social Software enables people to meet, connect or
collaborate through CMC
Identity - a way of uniquely identifying people in the
system
Presence - a way of knowing who is online, available or
otherwise nearby
Relationships - a way of describing how two users in
the system are related (e.g. in Flickr, people can be
contacts, friends of family)
Conversations - a way of talking to other people
through the system
Groups - a way of forming communities of interest
Reputation - a way of knowing the status of other
people in the system (who's a good citizen? who can be
trusted?)
Sharing - a way of sharing things that are meaningful to
participants (like photos or videos)
21 May 2007 (c) 2007, User Intelligence 6

7. PCW – Social IA – Gene Smith
Creators, synthesizers and Consumers
1% creators
10% synthesizers
100% consumers
21 May 2007 (c) 2007, User Intelligence 7

8. PCW – Social IA – Gene Smith
Three ingredients for social IA
• Capture user actions
Things people do that we can track
Popularity – Community – Reputation
Ignore higher goals & motivations
• Aggregate and display
Bring together user action in a relevant way
Display them
Rules
• Feedback
Positive & negative feedback
Feedback loops
21 May 2007 (c) 2007, User Intelligence 8

9. PCW – Social IA – Thomas VanderWal
Interesting:
Who tags?
• As much as 28% of Americans have tagged
• Daily, 7% of people on the web in US tag
• Why?
Their own use/value
Add perspective/content
Refindability
State interest
Sociality
21 May 2007 (c) 2007, User Intelligence 9

10. 21 May 2007 (c) 2007, User Intelligence 10

11. 21 May 2007 (c) 2007, User Intelligence 11

12. Conference sessions
• 45 presentations
• 6 panels
• Flex track
For this presentation we focus on
• data driven IA
• Documenting (rich) IA
21 May 2007 (c) 2007, User Intelligence 12

13. Conference sessions – Data-driven IA
• 4 sessions
21 May 2007 (c) 2007, User Intelligence 13

14. 1.Using search analytics to diagnose what's ailing your IA
Message:
• If you are not analyzing your searchlogs you are not
listening to your customers
• Search is too important to leave in the hands of
robots
SA Works like the Short head - Long tail graph
• Use ‘Best bets’ to help the short head (500 queries)
and sample the long tail for trends,and… watch out
for search engine politics
• Output of best bets to your site: Use best bets for A-
Z index! (http://www.msu.edu/)
21 May 2007 (c) 2007, User Intelligence 14

15. 1.Using search analytics to diagnose what's ailing your IA
Remarks/tips
• Never fixed: Seasonal search trends, update best bets every
week/month
• Use search logs or a special database/tool to analyze search
terms and search behavior.
• Voorbeeld campus map banner: preference for search box
over any other navigation
• Search results: #10 (10 on a page) is clicked more than #
6/7/8/9
• From which pages did users start a search?
• Update most frequently requested docs!
• Input for IA: Use SA to create a vocabulary, cluster 500 short
head and sample of 100 from long tail
21 May 2007 (c) 2007, User Intelligence 15

16. 2.Intelligent inter(RE)action:
An argument for a data-driven approach to UI design
Message:
• The Future of Design Will Be Data-Driven
• Become a data detective: find sources and testing
mechanisms
Segmentation surveys, comscore reports, search logs,
site traffic reports, google trends info, clickstreams &
clickdensity analysis, cookie & javascript data,
scrolling analysis etc etc.
Beta: fast online and optimize later: Multivariate
testing (example slide multivariate testing)
21 May 2007 (c) 2007, User Intelligence 16

17. ASIS&T Information Architecture Summit 2007
Product Release: Rough, Right & Ready For Change
Content
Boxes Above/Below Design of Button
Button
Control CONTROL CONTROL
1A 2A 3A
Rename headers Bullet list Alter copy
1B 2B 3B
and text links
Levels
Reduce to 3 and move 1C Remove $395 from Replace button
2C 3C
NOT READY below the 3 below button with text link
boxes
In Praise of Multivariate Testing!
17

18. 2.Intelligent inter(RE)action:
An argument for a data-driven approach to UI design
Do:
• Validate user persona
• Define quantitative success metrics early
There are no right answers, just ongoing testing
and refinement
21 May 2007 (c) 2007, User Intelligence 18

19. 3.Search engine optimization and IA:
the beginnings of a beautiful friendship
Web analytics show preference for search box over
any site navigation of any kind
Google: Pagerank caused a googlearchy but...
• Hilltop algorithm
• topic-sensitive pagerank
• Uses broad (learned) topics, authority pages and
hubs to counteract previous problems with pure
pagerank
Now It is All About Meaning!
We should not capitulate or cooperate but instead let
IA become a partner in developing search
technology that works with the user.
21 May 2007 (c) 2007, User Intelligence 19

20. 3.Search engine optimization and IA:
the beginnings of a beautiful friendship
Influence of Search engines on IA and
technology:
• Site Navigation Strategy
• Site Organization Strategy
• Link Strategy
• Page Code Strategy
• Content Strategy
• Metadata Strategy
21 May 2007 (c) 2007, User Intelligence 20

21. 4.Real information architecture, new mighty deeds
Panel session about data on the web
• Today real information architects’ mighty
deeds are moving from macro-organisation
of one web site for one organisation, to the
micro-organisation of information creating a
web of data.
• Get information/data from different places on
the web that is in some way related to
eachother
21 May 2007 (c) 2007, User Intelligence 21

22. 4.Real information architecture, new mighty deeds
Why open up data?
• Simply to get data out...
• Use APIs to drive people to your stuff
• Make your service more attractive and useful with less
central development
• Use syndicated content as a platform
• Turn your API into a pay-for service
Consequences
• Every new service can build on top of every other existing
service - the web becomes a true platform
• Every service and piece of data that’s added to the web
makes every other service potentially more powerful
21 May 2007 (c) 2007, User Intelligence 22

23. 4.Real information architecture – new mighty deeds
A virtuous circle
• Massive creative possibilities
• Accelerating innovation
• Increasingly competitive services
• Increasingly componentised services
• Increasingly specialised services
21 May 2007 (c) 2007, User Intelligence 23

24. 4.Real information architecture – new mighty deeds
Impacts on IA (data)
• Operating within an ecosystem
• Always engaging with (simple) standards
• Always focusing on data for reuse out with
the local site
• Data designed in weblike ways
21 May 2007 (c) 2007, User Intelligence 24

25. 4.Real information architecture – new mighty deeds
Impacts on IA (site)
• Site is public expression of data
• Site must be entry point for users, developers
and machines
• Sites of objects, relationships and object
‘manipulators’
• Manifesting the human path through the data
21 May 2007 (c) 2007, User Intelligence 25

26. 4.Real information architecture – new mighty deeds
Weblike Data
• Atomic: parcels of data that can stand alone
• Global Identifiers: data you can link to
• Hyperlinked: points to related data
• Web-shaped: interconnected, with no hierarchy and
no single starting-point
Examples: blogs, delicious, upcoming, flickr, last.fm,
twitter, etc to find out about someone.
21 May 2007 (c) 2007, User Intelligence 26

27. 21 May 2007 (c) 2007, User Intelligence 27

28. Documenting rich IA
1 session
21 May 2007 (c) 2007, User Intelligence 28

29. Communicating design:
an astonishingly close look at what makes IA documentation work
The role of documentation
• Consistency of Vision
Documents help facilitate communication
• Accountability
Documents represent project history
• Traceability
Documents show progress
21 May 2007 (c) 2007, User Intelligence 29

30. Communicating design:
an astonishingly close look at what makes IA documentation work
Different kinds of documents:
Usability Test Plan
Usability Report
Concept Model
Screen Design Site Map
Persona
Flow Chart
Competitive Analysis
Content Inventory
Wireframe
21 May 2007 (c) 2007, User Intelligence 30

31. Communicating design:
an astonishingly close look at what makes IA documentation work
User Needs Strategy Design
Persona Competitive Analysis Site Maps
Usability Test Plan Concept Model Flow Charts
Usability Reports Content Inventory Wireframes
Screen Designs
What do users want? What approach What does the
Does it meet their needs? should we take? solution look like?
21 May 2007 (c) 2007, User Intelligence 31

32. Communicating design:
an astonishingly close look at what makes IA documentation work
Creating deliverables
Establish purpose
•
Identify audience
•
Inventory contents
•
Prioritize contents
•
Create visual language
•
21 May 2007 (c) 2007, User Intelligence 32

33. Communicating design:
an astonishingly close look at what makes IA documentation work
Using deliverables
Communicate purpose
•
Relinquish control
•
Note opportunities for
•
improvement
Estimate value of
•
maintenance
21 May 2007 (c) 2007, User Intelligence 33

34. Userintelligence workshop/flextrack: Swipr!
21 May 2007 (c) 2007, User Intelligence 34

35. swipr.com intuitect.com axure.com
21 May 2007 (c) 2007, User Intelligence 35

36. 21 May 2007 (c) 2007, User Intelligence 36