1. William H. Bowers – whb108@psu.edu Modeling Users: Personas and Goals Cooper 5

2. William H. Bowers – whb108@psu.edu Topics Why Model? Why Model? Personas Personas Personas as a Design Tool Personas as a Design Tool Personas vs. User Roles Personas vs. User Roles Personas vs. Market Segments Personas vs. Market Segments User vs. Non-User Personas User vs. Non-User Personas

3. William H. Bowers – whb108@psu.edu Topics Goals Goals User Goals User Goals Non-User Goals Non-User Goals Constructing Personas Constructing Personas Persona Types Persona Types Other Models Other Models Questions & Discussion Questions & Discussion

4. William H. Bowers – whb108@psu.edu Why Model? Represent complex structures, relationships Represent complex structures, relationships Increased understanding, visualization Increased understanding, visualization Based on raw, observed behavior Based on raw, observed behavior Synthesize data patterns Synthesize data patterns

5. William H. Bowers – whb108@psu.edu Personas Help identify specific users and needs Help identify specific users and needs Identify primary, secondary users Identify primary, secondary users Helps choose the right individuals to design for Helps choose the right individuals to design for

6. William H. Bowers – whb108@psu.edu Personas as a Design Tool Identify what the product should do Identify what the product should do Determine a product’s behavior Determine a product’s behavior Facilitates communication with stakeholders Facilitates communication with stakeholders Builds consensus and commitment Builds consensus and commitment Measures design effectiveness Measures design effectiveness

7. William H. Bowers – whb108@psu.edu Personas as a Design Tool Contributes to marketing and sales Contributes to marketing and sales Help resolve Help resolve –Elastic user –Self-referential design –Design edge cases

8. William H. Bowers – whb108@psu.edu The Elastic User Each designer has own idea of end user Each designer has own idea of end user User definition becomes elastic to fit designer User definition becomes elastic to fit designer Real users are not elastic Real users are not elastic

9. William H. Bowers – whb108@psu.edu Self-Referential Design Designers project own goals onto product Designers project own goals onto product We tend towards technology for it’s own sake We tend towards technology for it’s own sake

10. William H. Bowers – whb108@psu.edu Design Edge Cases Possible situations Possible situations Usually not experienced by target personas Usually not experienced by target personas Must be programmed for Must be programmed for Not the design focus Not the design focus

11. William H. Bowers – whb108@psu.edu Personas are Based on Research Interviews with users Interviews with users Information from stakeholders Information from stakeholders Information from SMEs Information from SMEs Market research data Market research data Market segmentation models Market segmentation models Literature reviews Literature reviews

12. William H. Bowers – whb108@psu.edu Personas are Represented as Individuals User models treated as actual individuals User models treated as actual individuals Represented as specific individuals Represented as specific individuals Considered as real users Considered as real users Represent classes of users in context Represent classes of users in context Context specific Context specific

13. William H. Bowers – whb108@psu.edu Personas are Represented as Individuals Not reusable across products Not reusable across products Not archetypes or stereotypes Not archetypes or stereotypes Do not represent an average user Do not represent an average user Represent user examples Represent user examples May have a collection or cast of personas for a product May have a collection or cast of personas for a product

14. William H. Bowers – whb108@psu.edu Personas vs. User Roles Some similarities Some similarities –Seek to describe relationships of users to products Roles are abstractions Roles are abstractions Personas address goals Personas address goals Personas are more holistic models Personas are more holistic models

15. William H. Bowers – whb108@psu.edu Personas vs. Market Segments Market segments are based on Market segments are based on –Demographics –Distribution channels Personas are based on Personas are based on –Behaviors –Goals

16. William H. Bowers – whb108@psu.edu User vs. Non-User Personas Non-user personas include Non-user personas include –Product reviewers –Columnists –IT Managers –Purchasing agents Driven by business goals Driven by business goals

17. William H. Bowers – whb108@psu.edu Goals Drivers behind user behaviors Drivers behind user behaviors Addressed via tasks Addressed via tasks Provide answers to product usage motivation Provide answers to product usage motivation Inferred from qualitative data Inferred from qualitative data Expressed as simple sentence Expressed as simple sentence

18. William H. Bowers – whb108@psu.edu Types of Goals First priority in design First priority in design Goals may be different for: Goals may be different for: –Organizations –Employers –Customers –Partners –End users

19. William H. Bowers – whb108@psu.edu User Goals Life goals Life goals –Become an expert in my field –Get promoted quickly –Exhibit ethics and trust

20. William H. Bowers – whb108@psu.edu User Goals Experience goals Experience goals –Don’t feel stupid –Minimize or eliminate mistakes –Feel competent and confident –Enjoy the product’s use

21. William H. Bowers – whb108@psu.edu User Goals End goals End goals –Find the best price for a product –Finalize a press release –Process customer orders –Create software

22. William H. Bowers – whb108@psu.edu Non-User Goals Customer Customer –Parents, relatives, friends –IT Managers, purchasers, management Security Security Maintenance Maintenance Customization Customization Installation Installation

23. William H. Bowers – whb108@psu.edu Non-User Goals Corporate Corporate –Increase profit –Increase market share –Defeat competition –Use resources efficiently –Offer more products or services

24. William H. Bowers – whb108@psu.edu Non-User Goals Technical goals Technical goals –Minimize memory use –Run in a browser –Safeguard data –Execute efficiently –Cross platform usage/consistency

25. William H. Bowers – whb108@psu.edu Constructing Personas Incorporate information about Incorporate information about –Goals –Attitudes –Work or activity flow –Environment –Skills and levels –Frustrations

26. William H. Bowers – whb108@psu.edu Constructing Personas Revisit the personal hypothesis Revisit the personal hypothesis Map interviews to behavioral variables Map interviews to behavioral variables Identify significant behavior patterns Identify significant behavior patterns Synthesize characteristics and goals Synthesize characteristics and goals Check for completeness Check for completeness Develop narratives Develop narratives Designate types Designate types

27. William H. Bowers – whb108@psu.edu Revisit The Personal Hypothesis Compare patterns to assumptions Compare patterns to assumptions Do not focus on demographics Do not focus on demographics Behavioral variables are paramount Behavioral variables are paramount 15 – 30 variables per role are typical 15 – 30 variables per role are typical

28. William H. Bowers – whb108@psu.edu Map Interviews To Behavioral Variables Map interviewee against variable range Map interviewee against variable range Precision is not critical Precision is not critical Relative placement is the goal Relative placement is the goal

29. William H. Bowers – whb108@psu.edu Mapping Subjects to Variables

30. William H. Bowers – whb108@psu.edu Identify Significant Behavior Patterns Clustering of subjects may ID persona Clustering of subjects may ID persona Clustered behaviors must be causal Clustered behaviors must be causal

31. William H. Bowers – whb108@psu.edu Synthesize Characteristics And Relevant Goals Describe such things as Describe such things as –Potential use environment –Typical workday –Current solutions –Frustrations with existing systems –Relevant relationships with others

32. William H. Bowers – whb108@psu.edu Check For Completeness Merge or separate personas Merge or separate personas Fill in gaps Fill in gaps Insure distinctness and completeness Insure distinctness and completeness

33. William H. Bowers – whb108@psu.edu Develop Narratives Third person narrative Third person narrative One to two pages One to two pages Not a short story Not a short story Introduces persona Introduces persona Sketches a day in the life Sketches a day in the life Expresses personas product expectations Expresses personas product expectations

34. William H. Bowers – whb108@psu.edu Designate Types Primary Personas Primary Personas Secondary Personas Secondary Personas Supplemental Personas Supplemental Personas Customer Personas Customer Personas Served Personas Served Personas Negative Personas Negative Personas

35. William H. Bowers – whb108@psu.edu Primary Personas Primary target for interface design Primary target for interface design Multiple interfaces for multiple primary personas are possible Multiple interfaces for multiple primary personas are possible Not satisfied by designs targeted to any other persona Not satisfied by designs targeted to any other persona Compare goals of different personas Compare goals of different personas

36. William H. Bowers – whb108@psu.edu Secondary Personas May be satisfied by 1 or 2 additions May be satisfied by 1 or 2 additions Address needs without impeding primary Address needs without impeding primary Typically, 0 - 2 Typically, 0 - 2

37. William H. Bowers – whb108@psu.edu Supplemental Personas Satisfied by primary personas’ interface Satisfied by primary personas’ interface May be peripheral stakeholders May be peripheral stakeholders

38. William H. Bowers – whb108@psu.edu Customer Personas Not end users Not end users Treated a secondary Treated a secondary May be primary personas May be primary personas

39. William H. Bowers – whb108@psu.edu Served Personas Not product users Not product users Directly affected by product’s use Directly affected by product’s use Served by interface Served by interface

40. William H. Bowers – whb108@psu.edu Negative Personas Non-users Non-users Purely rhetorical Purely rhetorical Communicates who is not the design target Communicates who is not the design target

41. William H. Bowers – whb108@psu.edu Other Models Workflow or sequence reflect Workflow or sequence reflect –Process initiation –Information produced and consumed –Decisions –Actions

42. William H. Bowers – whb108@psu.edu Other Models Artifact models Artifact models –Online or paper forms –Capture commonalities and differences –Useful to ID best practices Physical models Physical models –Focus on layout

43. William H. Bowers – whb108@psu.edu Questions & Discussion