Data Driven Personas Summit 08

Slide 1: data driven design research personas Todd Zaki Warfel, Messagefirst

Slide 2: “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

Slide 3: “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

Slide 4: Personas are a representative behavior and activity profile that are contextual and specific to the particular application or service.

Slide 5: Personas are a representative behavior and activity profile that are contextual and specific to the particular application or service.

Slide 6: Why use them?

Slide 7: The average user doesn’t exist.

Slide 8: They keep you out of user.

Slide 9: They keep you out of user.

Slide 10: As a design research tool, they are a powerful way to communicate knowledge, activities, interests, influencers, goals, and pain points.

Slide 11: As a design research tool, they are a powerful way to communicate knowledge, activities, interests, influencers, goals, and pain points.

Slide 12: Design research personas can be used for design

Slide 13: They can be used for research

Slide 14: Design research personas can be used for recruiting

Slide 15: Design research personas can be used for training

Slide 18: Tips for making better data-driven personas.

Slide 19: Multiple sources keep things in balance.

Slide 20: Internal sources can be stake holders, web analytics, and customer support.

Slide 21: External sources can be customers and someone you know.

Slide 22: Basing them on someone you know keeps them grounded and more realistic.

Slide 23: Only build what you need.

Slide 24: Getting it all on one page is tricky.

Slide 26: Alex Program Manager Key Characteristics Do Te ma ch in no Kn lo o gy wle Lifecycle Kn dg ow e Goals Jan le Ex dg pe e rie Questions nc e Knowledge Co 1 2 3 4 5 nf ig u Sa rato le r Ac sfor Su tiv ce bm e itt Job Jul ed s Re Jo po bs rt G e Ma n il Gr era ea to tP r la in s Activities and Interest PD P CS M A Dec an Fil tis e P At Pr roc las o e Pr gra ssin og m g ra m Se Sp Ch tup ec an ia Managers l In ges vo Influencers Month ice Applications s 1.0 Implementation they have enough funds to run the file.” “Most of my time is spent figuring out if Do Te ma ch in no Kn lo o Lifecycle gy wle Kn dg Jan ow e le Ex dg pe e rie nc e Knowledge Co nf 1 2 3 4 5 ig u Sa rato le r A sfo Su ctiv rce bm e Jul itt Job ed s Re Jo po bs rt G e Ma n il Gr era ea to tP r la in s Activities and Interest PD P CS Dec M A Frustrations & Pain Points an Fil tis e P At Pr roc las o e Pr gra ssin og m g ra m Se Sp Ch tup ec an ia l In ges Month vo ice s 2.0 Program Managers

Slide 27: Do Te ma ch in no Kn lo o Lifecycle gy wle Kn dg Jan ow e le Ex dg pe e r ie nc e Knowledge Co nf 1 2 3 4 5 ig u Sa rato le A sfo r Su ctiv rce bm e Jul itt Job ed s Re Jo po bs rt G e Ma n il Gr era ea to tP r la in s Activities and Interest PD P CS Dec M A an Fil tis e Pr Atl Pr oc as o e Pr gra ssin og m g ra m Set Sp Ch up ec an ia l In ges Month vo ice s

Slide 28: Make sure you test and validate your personas.

Slide 29: Reality check.

Slide 30: Are they someone you know?

Slide 31: I think we did lunch.

Slide 32: I talked to him on the phone last week.

Slide 33: Common Mistakes

Slide 34: Marketing vs. 1 design research personas

Slide 35: Large sets 2

Slide 36: 3 Too much personal information

Slide 37: 4 The recycle trap

Slide 38: 5 Not used throughout the process

Slide 39: data driven design research personas Todd Zaki Warfel, Messagefirst