The document discusses various methods to enhance user experience dimensions, emphasizing areas such as learnability, wayfinding, and responsiveness. It addresses the importance of understanding user behavior and creating intuitive system designs through methods like design anthropology and card sorting. The future of user interaction is linked to the evolution of semantic taxonomies, artificial intelligence, and improved categorization techniques.

1. Methods of evolving the user experience

2. Dimensions in user experience
 behavioral/attitudinal
 quantitative/qualitative
 innovative/adapted/traditional
 exploratory/generative/evaluative
 participatory/observational/self-reporting/
expert review/design process

3. Learnability
 Structuring a context for the system that
will make the features learnable by
nature is the goal of successful systems.
 Using messaging in an informal gestural
way to guide users and usher them is a
natural way to build learnable trust with
them.

4. Wayfinding
 Having the intuitive ability to traverse the
system without contextual
understanding would be the ideal state
to design the systems navigation.

5. Findability
 Layering in smart findability options and
bringing a understandable taxonomy will
help improve the systems overall
usefulness.
 Using tagging and semantic meta data
will improve the findable elements for
users of the system.

6. Usefulness
 Clearly the system has to be able to
support useful interactions between
users and their data.
 This means that there needs to be a
tangible and measure benefit as a
system output to the user.

7. Aesthetic
 The design aesthetic is a very subjective
matter. Lets see if we can quantify its
relativeness.
 The best design is something that
serves the user and helps to build a
relationship between the visual display
and the users data.

8. Responsiveness
 The perception of how good a system is
or how well it functions is a product of
how responsive the system is generally.
 Consider the weight of a user interface
and its interactions. Design lightweight
user interfaces that are relatively flat for
good experiences.

9. Efficacy
 Having an application that uses well will
lead to effective interactions between
the user and their objective
 Time to complete a transaction and the
amount of clicks to complete tasks will
be paramount in judging the efficiency of
a system.

10. Simplicity
 There is a lot to be said for a simple to
use application. There is a loss of
cognitive ability once a developer and
business requirements seep into a state
of feature glut.
 The target and goal should be to make
an application approachable and
understandable for a user to interact
with.

11. Forgiveness
 Provide an Undo command.
 Confirm commands for risky actions or
commands that have unintended
consequences
 Whenever practical, allow users to
correct mistakes easily.
 Have clear physical separation between
frequently used commands and
destructive commands.

12. Behavioral Patterns
 Layering patterns for a multidimensional
in-depth understanding of users.
 Preference partitioning
 Behavioral relationships to content
functionality
 Predictive trending patterns
 Action origins and predictive matching

13. Demographics
 Segmenting the user base and their
specific and unique criteria
 Sorting users based upon income, location,
age, Sex and predictive patterns
 Overlaying multiple data sources for a
more compelling picture of the users based
upon imperial data collected from
transactions
 Relating a multidimensional view with
combined data to build a compelling picture
of the end user of the system

14. Psychographic
 Understanding why users click and how
they react to elements within the system
 Documenting the cognitive reactions to
users trying to reach an objective within
the system context
 Leverage a psychographic
profile/persona for optimal system and
user interactions
 Build a catalogue of the psychographic
triggers of why users do certain actions

15. Psychographic
Considerations
 People Don't Want to Work or Think More
Than They Have To
 People Have Limitations
 People Make Mistakes
 Human Memory Is Complicated
 People are Social
 Attention
 People Crave Information
 Unconscious Processing
 People Create Mental Models
 Visual System

16. Ethnographic
 Building a contextual understanding on the
racial biases and preferences on system
usage
 Establish a baseline understanding of how
ethnic biases affect the users of our system
 Understand the ethnographic focal point
and narrative that is contextual to our users
 Construct observational methods that
enhance the discovery of relative pertinent
findings

17. Web Analytics
 Measuring the users response to design
implementations
 Multivariate A/B testing
 Click tracking
 User path analysis
 Bounce rates
 Geographic user segmentation
 Origin analysis (referring source)
 Content popularity (understanding what
content/functions are popular)

18. Design Anthropology
“Design Anthropology has a direct
correlation and basis for understanding
the genesis of your design and how it is
evolving”

19. Design Anthropology
 The six methods in applying a design
anthropology.
 Finding out and learning
○ Learning about previous products, contextual boundaries and providing insights
to the current state of the products.
 Giving Strategic Direction
○ Strategic and Analytics tasks that help identify, plan, set, review, analyze and
give a project direction.
 Developing Concepts
○ Developing Relevant, innovative ideas and concepts, creating solutions.
 Selecting the Best
○ Selecting ideas and combining concepts, evaluate results and solutions.
 Enabling understanding
○ Making concepts tangible, showing future possibilities and giving overviews.
 Make it happen
○ Implementation and delivery providing guidelines and plans

20. Interaction Development
 Before thinking outside the box you
must understand the box.
 Designing the interaction between
human and computer can be complex or
simple depending on the approach.
 These are the prefer methods to understand
how the interactions are established and
what the touch points are.
○ Task flows
○ Swim lane Diagrams

21. Taxonomy
Taxonomies are collections of
facets, which are created by
organizing concepts into
categories.

22. Taxonomy
Considerations for Implementation and execution of an applied
Taxonomy structure.
*Taxonomy isn't navigation it “Categorization and Classification of
information”
 Strategy: User Centered vs. Business Centered
 Size: Scalable vs. Finite
 Coverage: Comprehensive vs. Section Specific
 Application: Cross Channel vs. Web Centered
 Time Sensitivity: Aspirational vs. Current
 Metaphor: Uniform/Exact vs. Mixed Approach
 Language Conventions: SEO Preferential vs. Natural Language
vs. Branding vs. Authoritative
 Structure: Polyhierarchical vs. Mutually Exclusive

23. Taxonomy Governance
 Governance Plan
 Ensures the Taxonomy remains useful as business needs, content,
vendor input, or user expectations change or scale.
 • How it’s used
 • Who uses it
 • Why & When it might be updated
 • How it’s updated
 • Who updates it
 • Version tracking & archival considerations

24. Card sorting
Card sorting is one of the best ways to
identify categories by having
controlled tests with groups of users to
create categories.

25. Folksonomy
 Folksonomy solves the The Frustration with
Taxonomies
 Folksonomies: A New Approach (User Centric
Approach)
 Folksonomies Address Taxonomy Difficulties
 Applying Folksonomies in Other Areas is
Untested
We’re Optimistic about Folksonomies
“At this point, folksonomies are more of an
interesting technology than a tried-and-true
design tool.”

26. The Future of User
Interaction
 Semantic taxonomy.
 Semantic folksonomy.
 Applied historical machine learning.
 Artificial Intelligence, correlating web
artifact relationships.
 RDF/OWL web-objects that are
contextually self-aware

27. Thank you
Raymond A. Monaco
armadadigital.com
raymond@armadadigital.com
702-858-4479