User Persona Creation

Stakeholder-facing personas from research you already have. Do not invent demographics. Prefer Behavioral Persona From Research after affinity or insight statements; use this only when the room still wants a named persona card.

Open in ChatGPT

Prompt

Create detailed user personas based on the following research data:

[Paste research data: interviews, surveys, analytics, user observations]

For each persona, include:

1. Persona Overview
   - Name and photo/avatar description
   - Demographics (age, location, occupation, education)
   - Quote that captures their essence
   - Role and responsibilities

2. Goals and Motivations
   - Primary goals (what they want to achieve)
   - Secondary goals
   - Motivations (why these goals matter)
   - Success criteria

3. Pain Points and Frustrations
   - Current pain points
   - Frustrations with existing solutions
   - Barriers to success
   - Emotional responses

4. Behaviors and Habits
   - How they currently solve problems
   - Tools and platforms they use
   - Information consumption habits
   - Decision-making process

5. Needs and Expectations
   - What they need from a solution
   - Expectations and assumptions
   - Desired outcomes
   - Must-have vs. nice-to-have features

6. Context and Environment
   - When and where they use products/services
   - Physical and digital environment
   - Constraints and limitations
   - Influences and influencers

7. User Journey Touchpoints
   - Key moments of interaction
   - Emotional state at each touchpoint
   - Opportunities for improvement

Format as detailed, realistic personas with specific details and quotes from research.

How to use

  1. 1Run Affinity Mapping Assistant and Behavioral Persona From Research first. Only use this prompt if you still need a traditional persona one-pager. Never let the model invent age, job title, or quotes.
  2. 2Organize your research data: Collect interview transcripts, survey responses, analytics insights, or user observation notes
  3. 3Replace [Paste research data] with your organized data. Format: "Interview 1: [transcript]" "Survey responses: [data]" "Analytics insights: [findings]"
  4. 4Add context before the prompt: Describe your product and research goals. Example: "We're a B2B SaaS tool for project managers. Research goal: Understand how users manage multiple projects. Interviews: 10 participants."
  5. 5If you have existing personas: Paste your current personas. Say "Update these personas with new research: [paste personas] and [new research data]"
  6. 6Paste the modified prompt into your preferred AI tool, like ChatGPT or Claude (preferably with longer context if you have large datasets)
  7. 7Review the generated personas: Check demographics, goals, pain points, and behaviors
  8. 8Ask for refinements: Request "Create 2-3 personas from this data" or "Focus on primary vs secondary personas" or "Add more behavioral details"
  9. 9Export to your design tools: Copy personas to Figma, Miro, or your design system documentation
  10. 10Share with team: Use personas to align team around user needs and guide design decisions

Pro Tips

  • Include real user quotes: Paste interview quotes verbatim so personas feel authentic and grounded in research
  • Specify persona count: Mention "Create 2 primary personas" or "Create 3 personas (primary, secondary, edge case)"
  • For quantitative data: Include survey statistics (e.g., "80% of users said...") for data-driven personas
  • Request persona comparisons: Ask "Show differences between these personas" to identify unique needs
  • Save personas as templates: Reuse structure for future research by asking "Use the same format but for [new research]"
  • For behavior-first personas (JTBD, mental model, needs vs wants, no invented demographics), use Behavioral Persona From Research in Research.

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