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transcript
Incentive Architecture
Marianne SweenyTechNet/Servers Web Team
April 29, 2004
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Introduction
Agenda Information Behavior Models Emerging Trends in information architecture Search Where we are now Where we could be?
incentive Architecture “.. [is a ] unifying coherent structure that motivates users by taking advantage of persuasive tactics that will make them take action to help them make the right decisions”
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Information Seeking Model
Dervin’s Sensemaking
Users strive to make sense of reality as they move through situations, time, and space
Users encounter gaps in their knowledge and see these as barriers
Users seek to “bridge” the gap and reach their goal (a reality that again makes sense)
Information is what bridges the gap (provides answers, advice, help, etc)
Users deploy various strategies to build the bridge over the gaps
Ask friends or co-workers (#1 information resource) Go to other resources (print, Web, experts)
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Information Seeking Model
Bates’ Berrypicking A typical search evolves as information is gathered in bits
and pieces along the way Query – document – thought – revision – extension/revision
– requery – document…and so on Searchers use a variety of techniques and resources Sometimes they want more
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So, What’s the Difference Between Browsing and Searching? Browsing
Views pages one at a time Navigates sequentially through hyperlinks Self-guided through site space and dependent on
“browsing cues” [information scent] Iterative depending on information found along the way
Searching Initiated by entering a search query and viewing a list of
ranked results Specifics driven Results deprived of context Includes irrelevant results due from machine intervention User has to know the taxonomy to be successful
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What our own CuSat Tells UsFinding things on our site is a problem for many
of our users
June 1999: 40% cannot find what they are looking for 50% of the time June 2001: Devs 54% / ITPros 54% cannot find what they are looking for
50% of the time SQL Server (FY01Q4): 44% cannot find what they are looking for 50% of
the time August 2001 (CuSat Grand Report ): 44% cannot find what they are
looking for 50% of the time April 2002 (ProdCom Functionality FY02Q4): Ability to find information =
31% vsat / 21% dsat April 2002 (CuSat SQL Server): Ability to find information = 29% vsat /
19% dsat July-Dec 2003 (CDDG Online CuSat): Frequency of finding information =
26% always / 18% seldom; satisfaction with ability to find information 31% vsat / 19% dsat
March 2004 (TechNET Web visitor profiling): Found everything = 46%, Found something = 31%, Found nothing = 25%
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Emerging Trends in Information Architecture
Mental Models Page Paradigm Information Scent Transitional Volatility Effective View Navigation Captology
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Mental Models Made famous most recently by Don Norman People form mental models of themselves
how the world around them, and the things, in it work
Incomplete Unstable Without firm boundaries Unscientific Parsimonious
Our users bring their peculiar mental model of how our sites work with them when they visit
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Page Paradigm
Every user comes to a Web site with a goal in mind
On any given Web page the user will Click something that appears to take them
closer to their goal Click the BACK button
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Information Scent
Remote indications of target content in the form of out-links throughout the information structure
Users forage for content on our sites Use hyperlinks as proximal cues for distal content
Information Scent is a subjective assessment of the user
User’s actions towards their goal is informed and influenced by information scent How to Buy has a strong scent SQL Server’s inoperability with Windows Server 2003 has a
weak scent
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Transitional Volatility Occurs in any page to page transition Users are looking for “something” on the site
and are often unable to “predict” the most direct path to success
Navigational competition (left navigation, right navigation, embedded links, stand alone links, etc.)
Navigational overload = navigational mechanisms compete instead of coordinate with other mechanisms
Habituate --- Reorient --- Predict Local view navigation provides the optimal user
experience (showing only the present directory in detail)
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Effective View Navigation Navigational view is small and user short of
time Paths through navigation should be short “Where to go next” is central to user’s concern Navigability requires an interlocking Web of
set representation Conceptual perception so that the navigator can
decode mirroring and form an actual perception of the information set
Similarity-based Navigation Large-scale semantics dominate
More stress on granular labels
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Effective View and Transitional Volatility in Practice on Oracle
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Captology
Study of the persuasive nature of technology http://captology.stanford.edu/
How can Web sites change what people believe and what they do
Types of Web site credibility Presumed Reputed Surface Earned
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So, What Do We Know So Far? Users come to us with a goal which is usually to get help bridging an
information gap in their sensemaking model of the world Along the way to collecting information to help them bridge
this gap, they find other bits of information which may cause them to revise their original quest
Users come to our sites with a preconceived mental image of how the site is laid out and functions
Users tend to ignore all navigational aids to focus on the body content where they either find what they are looking for or a pointer or they hit the BACK button
Users follow a “scent” for the information that they desire Users have a small frame (fisheye lens) through which they
navigate and little time Page to page transitions introduce transitional volatility which is
not always bad – local navigation views, working in collaboration with other navigational mechanism, provides the user with a sense of location (not lost-ness) and that the site has more content
Web sites have “credibility” which can be used to persuade the user to take certain action or change the user’s belief about something
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Search
Enterprise vs. Web Search SharePoint Portal Server
“Up the road a piece” Not GPS
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Architecture or Information Architecture
The way Clients are looking to the future requires that we should study our client’s situation more than we have ever done before. If we are to succeed, we must learn a great deal about how clients are organized and what strategies underlie their way of doing business”
Lorraine JohnsonSwinburne University of Technology
School of Information TechnologyHawthorne, Australia
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Where Are We Now
Customer Verbatim Since the adoption of the Product Lifecycle
navigation across the Product sites, we’ve segmented and developed personas for our audience – do they map to each other?
What is the identity of the Product Sites?
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What About Our Sites? SQL Server Product Site Today
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But Wait, There’s More
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And Still More…
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Where We Could Be
Competitor Analysis Oracle IBM
A proposed IA for the Product sites utilizing concepts recently discussed
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Persuasive Architecture in Practice
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Persuasive Architecture in Practice
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SQL Server Maybe Later?
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Resources Used for This PresentationASIST Special Interest Group: Information Architecture Mail ArchivesSearching Versus Finding: Why Systems Need Knowledge to Find What you really Want;
Woods, W.A.; Sun Microsystems; http://research.sun.com/spotlight/2004-04-05.wwoods.html ; April 2004
Guiding Users with Persuasive Design; Perfetti, Christine; User Interface Engineering.com; http://www.uie.com/articles/chak_interview/; March 2003
Business Centered Design; Olsen, Henrik; Interaction Designer’s Coffee Break; http://www.guuui.com/issues/01_03.php; January 2003
Seductive Design for Web sites; Scanlon, Tara; User Interface Engineering.com; http://www.uie.com/articles/seductive_design/; July 1999
Persuasive Navigation; Lash, Jeff; Digital Web Magazine; http://www.digital-web.com/columns/iaanythinggoes/iaanythinggoes_2002-12.shtml; December 2002
Understanding the Seductive Experience; Khaslavsky, Julie, Shedroff, Nathan; Communications of the ACM; May 1999
Transitional Volatility in Web Behavior; Danielson, David; http://www.stanford.edu/~davidd/MastersThesis/ ; June 2002
Transitional Volatility in Web Behavior; Danielson, David; IT & Society; vol.1, issue 3, Winter 2003; http://www.ITandSocity.org
From the mind’s eye of the user: The Sense-Making qualitative-quantitative methodology; Dervin, Brenda;
In J. D. Glazier & R. R. Powell (Eds.), Qualitative research in information management (pp. 61-84). Englewood, CO: Libraries Unlimited. Reprinted in: B. Dervin & L. Foreman-Wernet (with E. Lauterbach) (Eds.). (2003). Sense-Making Methodology reader: Selected writings of Brenda Dervin (pp. 269-292). Cresskill, NJ: Hampton Press. (1992)
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Resources Used for the Presentation
The Design of Browsing and Berrypicking Techniques for the Online Search Interface; Bates, Marcia; http://www.gseis.ucla.edu/faculty/bates/berrypicking.html; 1989
Incorporating Navigation Research into a Design Method; Lombardi, Victor; ASIST IA Summit 2004; http://www.iasummit.org/finalpapers/13/13_Handout_or__final__paper.ppt
Conceptual Links Trump Hyperlinks; Patch, Kimberly; TRN Magazine.com; http://www.trnmag.com/Stories/2002/071002/Conceptual_links_trump_hyperlinks_071002.html July 2002
The Page Paradigm; Hurst, Mark; Goodexperience.com; http://www.goodexperience.com/columns/04/0219.pp.html; February 2004
Scent Trails; Olston, Chris, Chi, Ed; Carnegie Mellon Databases.com; http://www.db.cs.cmu.edu/Pubs/Lib/tochi03scenttrails/scenttrails.pdf ; 2001
Effective View Navigation; Furnas, George; School of Information, University of Michigan; http://www.google.com/url?sa=U&start=5&q=http://www.si.umich.edu/~furnas/Papers/CHI97-EVN.2.pdf&e=7764; March 1997
Navigation in Electronic Worlds; Jul, Susanne, Furnas, George; Navigation 1997 Workshop; http://www.si.umich.edu/~furnas/Papers/Nav97_Report.pdf