The document describes a persona modeling technique called A3 Persona Modeler. It allows designers to visualize users based on their attitudes, aptitudes, and abilities. The technique involves mapping example users onto a grid based on key attributes. This helps designers account for what different types of users bring to the design and ensure all important personas are considered. It can be used with minimal data to establish provisional personas. The technique provides a framework for discussing users and informing design decisions.

1. Persona Modeler
Revealing who is coming to your site
Dana Chisnell
@danachis
#makingsense
1
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2. Matthew
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3. Matthew
Attorney
House in Tel Aviv
Married
Loves his Blackberry
Hates email
Reads NYTimes on iPad
Addicted to Words With Friends
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4. Buying tickets on a
university web site
for the Big Game
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5. Edith
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6. Edith
Follows American sports, especially
baseball
Hates ESPN.com
Loves face-to-face online
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7. Dennis
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8. Dennis
Building contractor
Cell phone is for calling home
Very tuned in to current events
Sees no usefulness in Facebook
Recently more absent-minded
Difficulty doing standard calculations
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9. Jane
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10. Jane
1,000-acre farm
Tweets soil chemical readings
Tablet instrumented to aggregate data
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11. You: designer & developer
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12. You: designer & developer
How do you design for these people
based on what you know?
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13. You: designer & developer
How do you design for these people
based on what you know?
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14. You: designer & developer
How do you design for these people
based on what you know?
Think about each of the people as you
answer these questions:
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15. What can we say about how
persistent the person is?
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16. How pro-active will this person
be in solving problems?
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17. How easily will this person
become frustrated?
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18. How tech savvy is this person?
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19. How literate is this person in
the domain?
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20. Little data, lots of assumptions
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21. How old are they?
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22. How old are they?
Matthew
Blackberry-loving
attorney
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23. How old are they?
54
Matthew
Blackberry-loving
attorney
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24. How old are they?
54
Matthew Edith
Blackberry-loving ESPN.com-hating
attorney Hangouts fan
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25. How old are they?
54 83
Matthew Edith
Blackberry-loving ESPN.com-hating
attorney Hangouts fan
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26. How old are they?
54 83
Matthew Edith Dennis
Blackberry-loving ESPN.com-hating Facebookwhat?
attorney Hangouts fan
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27. How old are they?
54 83 28
Matthew Edith Dennis
Blackberry-loving ESPN.com-hating Facebookwhat?
attorney Hangouts fan
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28. How old are they?
54 83 28
Matthew Edith Dennis Jane
Blackberry-loving ESPN.com-hating Facebookwhat? Farmer nerd
attorney Hangouts fan
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29. How old are they?
54 83 28 60
Matthew Edith Dennis Jane
Blackberry-loving ESPN.com-hating Facebookwhat? Farmer nerd
attorney Hangouts fan
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30. Friday, March 1, 13

31. How old are they?
How educated are they?
How much money do they make?
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32. These don’t matter.
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33. If demographics don’t matter,
what do you do?
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34. Ask the right questions
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35. Ask the right questions
• persistence with tech
• tolerance for risk & experimentation
• how patient, how easily frustrated
• tech savviness, expertise
• strength of tech vocabulary
• physical or cognitive abilities
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36. Friday, March 1, 13

37. • Attitude
motivation, emotion, risk tolerance,
persistence, optimism or pessimism
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38. • Attitude
motivation, emotion, risk tolerance,
persistence, optimism or pessimism
• Aptitude
current knowledge, ability to make
inferences, expertise
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39. • Attitude
motivation, emotion, risk tolerance,
persistence, optimism or pessimism
• Aptitude
current knowledge, ability to make
inferences, expertise
• Ability
physical and cognitive attributes
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40. !
A3
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41. Technique
‣ Focus on the attributes that matter
‣ Account for what the user brings to the design
‣ Adjustable to context, relationships, domain
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42. Tool
‣ Framework to think about provisional or proto-
personas (little or no data)
‣ Schema to evaluate existing personas’ strength of
coverage
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43. Collaboration tool
‣ Do our personas cover all the right attributes?
‣ Have we heard from all the users we need to hear
from?
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44. Task +
functionality
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45. Task +
functionality
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46. Task +
functionality
Buying tickets on a
university web site for the
Big Game
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47. Task +
functionality
Buying tickets on a
university web site for the
Big Game
Home or visitor?
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48. Task +
functionality
Buying tickets on a
university web site for the
Big Game
Home or visitor?
Suites or Varsity Club?
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49. Task +
functionality
Buying tickets on a
university web site for the
Big Game
Home or visitor?
Suites or Varsity Club?
Student section?
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50. Task +
functionality
Buying tickets on a
university web site for the
Big Game
Home or visitor?
Suites or Varsity Club?
Student section?
Drunk girls section?
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51. Ask the right questions
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52. Ask the right questions
• Who is the most persistent when it comes to working
with technology?
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53. Ask the right questions
• Who is the most persistent when it comes to working
with technology?
• Who is the most likely to experiment and create
workarounds when something doesn’t work the way
they expect?
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54. Ask the right questions
• Who is the most persistent when it comes to working
with technology?
• Who is the most likely to experiment and create
workarounds when something doesn’t work the way
they expect?
• Who do you think will give up when they encounter
frustrations out of impatience?
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55. Ask the right questions
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56. Ask the right questions
• Which one has the most tech expertise? Which one
strikes you as the least tech savvy?
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57. Ask the right questions
• Which one has the most tech expertise? Which one
strikes you as the least tech savvy?
• Which one is the most likely to call tech support to help
them get out of some tech pickle?
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58. Ask the right questions
• Which one has the most tech expertise? Which one
strikes you as the least tech savvy?
• Which one is the most likely to call tech support to help
them get out of some tech pickle?
• Who will have the most advanced tech vocabulary
when they do call for support?
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59. Matthew
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60. Matthew
Attorney
House in Tel Aviv, married
Assistant books reservations
Loves his Blackberry
Hates email
Reads NYTimes on iPad
Addicted to Words With Friends
Doesn’t spend a lot of time on the Web
Avid hiker and birder
Bad knees
Needs Rx eyepiece for scope
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61. !
Where does Matthew fit?
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62. M
!
Where does Matthew fit?
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63. M
M
!
Where does Matthew fit?
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64. M
M
M
!
Where does Matthew fit?
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65. Edith
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66. Edith
Avid sports fan
Follows Detroit Tigers
Hates ESPN.com
Loves face-to-face online
Picked up Skype early, quickly
Prefers Google Hangouts
Dropped FaceTime -
gestures were frustrating
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67. !
Where does Edith fit?
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68. E
!
Where does Edith fit?
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69. E
E
!
Where does Edith fit?
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70. E
E
E
!
Where does Edith fit?
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71. Dennis
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72. Dennis
Building contractor
Married to a nurse
They have 2 kids
8-year-old cell phone
Gets current events on the Web
Sees no usefulness in Facebook
Trouble sleeping, easily distracted
Served in the military:
Blunt Force Brain Trauma
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73. !
Where does Dennis fit?
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74. D
!
Where does Dennis fit?
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75. D
D
!
Where does Dennis fit?
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76. D
D
D
!
Where does Dennis fit?
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77. Jane
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78. Jane
1,000-acre farm
12 different systems every day
Tweets soil chemical readings
Smartphone alerts from exchanges
Tablet instrumented to aggregate data
Minimized manual input
Arthritic thumbs
Needs stronger progressive lenses
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79. !
Where does Jane fit?
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80. J
!
Where does Jane fit?
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81. J
J
!
Where does Jane fit?
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82. J
J
J
!
Where does Jane fit?
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83. !
A3 Persona modeling
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84. M
M
M
!
A3 Persona modeling
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85. M E
M E
E M
!
A3 Persona modeling
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86. D M E
DM E
D E M
!
A3 Persona modeling
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87. D M E J
DM E J
MJ
D E
!
A3 Persona modeling
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88. How do
design
decisions
change with
these
attributes?
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89. How do
design
decisions
change with
these
attributes?
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90. Friday, March 1, 13

91. Subtlety of
affordances
Size of targets
Directness of the
happy path
Feedback modalities
Labeling & trigger
words
Amount of copy
Wording of
instructions &
messages
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92. Friday, March 1, 13

93. If you had this tool, what would you do
next?
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94. If you had this tool, what would you do
next?
What would be different for your
design?
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95. A3 Persona modeler
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96. A3 Persona modeler
• Designing for attitude, aptitude, & ability
• Accounting for what the user brings to the design
• Checking that personas cover the right things
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97. Big ideas
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98. Big ideas
Persona modeler: fast way to visualize users by
asking important questions
framework for talking about who users are
can tell which users might be missing
works with any amount of data
middle ground between demographics and
research-based personas
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99. Where to learn more
Dana’s blog: http://
usabilitytesting.wordpress.com
Download templates, examples, and
links to other resources from
www.wiley.com/go/usabilitytesting
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100. Dana
Chisnell
dana@usabilityworks.net
www.usabilityworks.net
415.519.1148
@danachis
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