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Personas and Alternatives

As part of my Business Analysis upskilling, I recently took a deep look at the practice of using personas to model customers and end-users.

Personas are fictional characters, which you create based upon your research in order to represent the different user types that might use your service, product, site, or brand in a similar way. Creating personas will help you to understand your users’ needs, experiences, behaviors and goals.” – Product Manual

PRIMARY PURPOSES

  1. To build empathy within the product team by providing a deeply human face to what might otherwise be nameless and largely forgotten customers and end-users.
  2. To serve as engaging actors for user stories or use cases. Using personas motivates higher-quality and more complete story coverage, contrast to the bland “As a user I want to…”

Credits: Xtensio, Jerry Cao, Adobe, Mockplus

TYPICAL COMPONENTS

  • A fictitious name; sometimes with a memorable adjective pairing, e.g. “Impatient Isaac”.
  • A photograph
  • Demographics — e.g. age, gender, geographic location, salary or socioeconomic status, marital status, languages spoken, etc.
  • Occupation or role — e.g. software developer or single mom.
  • Brief bio — e.g. education, years in role, previous employment, etc.
  • Hobbies or affiliations. — e.g. avid runner, sings in a church choir, active in local SME (Society of Manufacturing Engineering) chapter, etc.
  • Defining adjectives — e.g. diligent, outspoken, skeptical, etc.
  • Personality profile — e.g. Deloitte Business Chemistry, DISC, Enneagram, Myers-Briggs Type Indicator(albeit widely discredited), or StrengthsFinder, etc.
  • Motivations — e.g. work-life balance, career advancement, status and recognition, membership and belonging, etc.
  • Technology comfort-level (use for technical products).
  • Behaviors / beliefs / fears that are relevant to product use — e.g. “Typical day is filled with back-to-back meetings”, “Must leave work by 4:30 to pick-up daughter from an after-school program”, “Values facts and data over opinions”, etc.
  • Pain / Challenges / Frustrations that the product might mitigate.
  • How does the persona currently solve the problem (the job that the product is being “hired” for)?
  • Usage patterns for any existing or competitor solutions.
  • Expected benefits that the product would provide.
  • Goals that the product would help the person achieve.
  • Influencers, i.e. who or what would trigger the persona to try the product?
  • Favorite social media, movies, books, TV shows, brands, etc.
  • A memorable pithy quote — e.g. “You have two minutes to convince me”.
  • Relationship to other personas. Sometimes shown on a 2×2 matrix.

For deeper look at largely the approach above, see the 18-page Persona Creation and Usage Toolkit, by George Olsen (2004).

CRITICISM AND ALTERNATIVES

  • Kim Flaherty writes for the Nielsen Norman Group about five common persona failure patterns and how to avoid them. The common failures are personas being created but not used, no buy-in from leadership, creation in a silo and imposed on people, lack of understanding of the what and why, and irrelevant data or lacking context in the persona.
  • Margaret Price and Doug Kim at Microsoft say that personas “are inherently an amalgamation, an average of attributes that we imagine our average customer has. And there’s no such thing as the average customer.” They recommend to “kill your personas…and adopt a model of persona spectrums. …persona spectrums focus our attention on a range of customer motivations, contexts, abilities, and circumstances.”
  • Sarah Dzida writes “personas have their positive and negative attributes. One of the greatest criticisms leveraged against them is that they often end up forgotten in drawers after initial team excitement.” Sarah then digs further into the Microsoft persona spectrum concept.
  • Michelle Gilmore and Adelaide Vinay at Neoteny provide an example of a “client [who] was confident that age defined attitudes towards digital security. After investigation, it became clear that it was risk appetite, not age, that was dividing people. Age was irrelevant — an 80-year-old had the same view as an 18-year-old. Stereotypes (personas) were impairing this client’s judgment.” Michelle and Adelaide offer behavioral profiling, a concept similar to Microsoft’s spectrums, as a way to move away from this sort of stereotyping.
  • Radina Doneva also advocates for focusing on behaviors, saying “The term behavioral archetype is more accurate as it relates to a typical example of customer behaviors which is characteristic for a group subset of the audience, whereas the term persona stands for a representation of an individual person which carries a lot of subjectivity.”
  • Jared Spool argues that when it comes to personas, the real value is in the scenarios and that “by starting with stories, we can get to the shared understanding we need to delivering great products and services.” Jared provides a powerful example of two people traveling by plane. Compared to personas with attributes like the list above, the two scenarios give a more memorable and useful context for a proposed product or service related to airline travel.
  • Alan Klement, who is known for “jobs to be done”, also advocates for removing the typical demographics and de-emphasizing, or not including, the typical photo. Indi Young makes similar recommendations in her 2016 article Describing Personas.

My next task is to apply the above thinking in an example for my fictitious company and people profile application.

Published in Business Analysis Resources

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