6. Language
States
current
+
future
Design / Artifacts
Validate
Academy of
Learning
Values
Beliefs
Behaviors
Roles
Human
Qualities
Toolkits
A Human Practice
7. Goals Design Metrics Assumptions
Core
Principles
Profiles Meaning
Stories
Features +
Prioritization
Task Models Journey
Maps
Designs
Patterns
Standards
Artifacts
META
CUSTOMER
DESIGN
THE PROJECT
ROOM
11. User Stories & goals
Interactions & Touch-points
Pain points
Products & Services
Interfaces
Gaps
Systems
Platforms
12. Customer
Journey
Interviews
Personas
Tools +
Artifacts
Listening Translation What did we
learn?
What does
it mean for
our
practice?
Project
Protocols
Stories
Observation
19. Early in
Project
Many Users
Summative testing
Stakeholder interviews
Comparative
benchmarking
Card sorting
User observation
Few Users
Satisfaction surveys
Market research
Iterative evaluation of
prototypes
Evaluation
of Designs
Ethnography
Walkthroughs
Expert
Reviews
21. Planning is critical
Item Why
Research themes UXD Agenda
Immediate questions Fixes
Stretch questions Product Strategy
What to do with results Impact
Known or unknown Gaps
Assumptions Body of Evidence
Other research Connecting data points
Design Impact
Observations & Insights Body of Evidence over time
23. Understanding people
Item Why
Beyond discussion guide Peripheral goodies
Not research Conversations
Good conversations Flow to get to goodies
Be Present Interested and aware
Time needed to … Trust
User need first … Not domain first, beyond
functions
You are not the expert User being interviewed
helps drives part of the
conversation
25. Capturing Stories
Item Why
Call before Get to know
Listening between the cracks … Emotions, people,
relationships, motivations,
issues
Your product & service is not their
priority
How it fits into their lives is
Clues towards … and task mapping Issues, motivations,
opportunities
Boundaries Beyond what we see now
27. Stories to Observations
Item Why
Transcribe stories Getting intimate with the
data
Reading stories (take turns) Capturing and listening
Emotional words Drivers to do things people
care about
Elements to unpack later Need for more detail (future
research?)
Quotes Personas
Artifacts Mapping data to its relevant
buckets
Time consuming + washing the data Good! Worth it!
28. Participant No
Age Range
Profession
Description
Describe the domain
Influencers
Story 1
Story 2
Story 3
Issues
Observations
Wish list
Opportunities/
Improvements
Story Sheets
30. Observations to Insights
Item Why
Post it notes to the wall Capture and movement and
space
Moving bits To see the data and group
and connect
Structuring Map to deliverables
Tell stories around the bits Deeper dives
Gaps Identify a need to discover
more in the future
32. Group Observations into
Insights
Item Why
Refining Clarity
Rinsing the data Clarity
Revisiting story sheets Missing bits
Grouping again New connections
Moving to XLS Clarity