Data Driven Personas

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    Data Driven Personas - Presentation Transcript

    1. Data-Driven Design Research Personas UPA 2007
    2. What. Why. Where.
    3. What is a persona?
    4. “A persona is a user archetype you can use to help guide decisions about product features, navigation, interactions, and even visual design.” - Kim Goodwin, Cooper
    5. Personas are a representative behavior and activity profile for a customer base.
    6. Personas are contextual and specific to the particular application or service.
    7. Why do we have them?
    8. The average user doesn’t exist.
    9. Keeping the you out of user and customer.
    10. What kinds of personas are there?
    11. Marketing & design research
    12. As a design research tool, they are a powerful way to communicate knowledge, activities, interests, influencers, goals, and pain points.
    13. Design research personas can be used for design
    14. Design research personas can be used for research
    15. Design research personas can be used for recruiting
    16. Design research personas can be used for customer service
    17. Design research personas can be used for training
    18. Design research personas are
    19. Design research personas are data-driven
    20. Design research personas are not a set of demographics
    21. Knowledge. Activities. Interests. Influencers. Goals. Frustrations and pain points.
    22. Where does the data come from?
    23. Design research personas include multiple data sources
    24. Both internal...
    25. Key stakeholders, web analytics, and customer support.
    26. ...and external
    27. The customer, customer advocate, and someone you know.
    28. Presenting the Data
    29. Do Te ma in ch no Kn o lo gy wle K n dg ow e le Ex dg pe e In rie te nc e rn al Re se a 1 2 3 4 5 In rch T tra ne ool tS s ea rc Co m m Go h un og ity le Pa ge s Bl og s IM Em ai l Ph Sh o a re ne d Dr ive s Co nf id en ce 1 2 3 4 5 & T Pr od rust uc tiv it y Co m m Re u so Th nit ur y e ce M Sou an ag rce em en t
    30. How do you test and validate your design research personas?
    31. The reality check.
    32. The someone you know check.
    33. Did we have lunch together yesterday?
    34. Have you spoken to them on the phone recently?
    35. Stages of the Persona Life-cycle
    36. Okay, so I have my design research personas. Now what?
    37. Development
    38. Birth
    39. Maturation
    40. Retirement
    41. Common Pitfalls and Mistakes
    42. Marketing vs. research design personas
    43. Large persona sets
    44. Too much personal information
    45. The recycle trap
    46. Not used throughout the design research process
    47. Exercise: Persona Shootout
    48. Michael Do Te ma in ch no Kn o lo gy wle Kn dg ow e le Ex dg pe e rie nc e Knowledge Pr od u 1 2 3 4 5 Ne ct T w ra in P Pr rod ing od uc Al uct t In f te rn Sel o ec at e tio n Co Sel e m pe ctio ns tit iv Ca e In Ac se S tel t ce ss udi or es y Qu Fin Activities and Interest de ot e Bu r ild e Re r po rts 1.0 Highly Seasoned Do Te ma in ch no Kn o lo gy wle Kn dg ow e le Ex dg pe e rie nc e Knowledge Pr od u 1 2 3 4 5 Ne c t T w ra in P Pr rod ing od uc Al uct t In f te rn Sel o ec at e tio n Co Sel e m pe ctio ns tit iv Ca e In Ac se S tel t ce ss udi e or yF s in Qu Activities and Interest de ot e Bu r ild e Re r po rts
    49. Exercise: Segmentation and Patterns
    50. The Hunter Gatherer
    51. Do Te ma in ch no Kn o lo gy wle Kn dg ow e le Ex dg pe e In rie te nc e rn al Re se a 1 2 3 4 5 In rch T tra ne ool tS s ea rc De pa Go h o rtm en gle tP ag es Bl og s IM Em ai l Sh Ph o ar ed ne Dr ive s Co nf id en ce 1 2 3 4 5 & T Pr od rust uc tiv ity Co m m Re u so Th nit ur y e ce M Sou an ag rce em en t
    52. The Worker Bee
    53. Do Te ma in ch no Kn o lo gy wle Kn dg ow e le Ex dge pe rie In te nc e rn al Re se a 1 2 3 4 5 In rch T tra ne ool tS s ea rc De pa Go h o rtm en gle tP ag es Bl og s IM Em ai l Sh Ph on ar e ed Dr ive s Co nf id en ce 1 2 3 4 5 & T Pr od rust uc tiv ity Co m m Re u so Th nit ur y e ce M Sou an ag rce em en t
    54. The Hive Tender
    55. Do Te ma in ch no Kn o lo gy wle Kn dg ow e le Ex dge pe rie In te nc e rn al Re se a 1 2 3 4 5 In rch T tra ne ool tS s ea rc De pa Go h o rtm en gle tP ag es Bl og s IM Em ai l Sh Ph on ar e ed Dr ive s Co nf id en ce 1 2 3 4 5 & T Pr od rust uc tiv ity Co m m Re u so Th nit ur y e ce M Sou an ag rce em en t
    56. The Librarian
    57. Do Te ma in ch no Kn o lo gy wle K n dg ow e le Ex dge pe rie In te nc e rn al Re se a 1 2 3 4 5 In rch T tra ne ool tS s ea rc De pa Go h o rtm en gle tP ag es Bl og s IM Em ai l Sh Ph o ar ed ne Dr ive s Co nf id en ce 1 2 3 4 5 & T Pr od rust uc tiv ity Co m m Re u so Th nit ur y e ce M Sou an ag rce em en t
    58. The Supporter
    59. Do Te ma in ch no Kn o lo gy wle Kn dg ow e le Ex dge pe rie In te nc e rn al Re se a 1 2 3 4 5 In rch T tra ne ool tS s ea rc De pa Go h o rtm en gle tP ag es Bl og s IM Em ai l Sh Ph on ar e ed Dr ive s Co nf id en ce 1 2 3 4 5 & T Pr od rust uc tiv ity Co m m Re u so Th nit ur y e ce M Sou an ag rce em en t
    60. Exercise: Creation
    61. Create personas for a Company Intranet
    62. Create personas for a mobile communication product/service
    63. Don’t forget their Knowledge. Activities. Interests. Influencers. Goals. Frustrations and pain points.
    64. Ready. Set. Go.
    65. Exercise: Presentation and Critique
    66. Data-Driven Design Research Personas UPA 2007

    + Todd ZakiWarfelTodd ZakiWarfel, 3 years ago

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