Playbook

User Persona Generator

Generate detailed user personas with goals, frustrations, behaviors, and design implications from a product description.

User Persona Generator

Create realistic, actionable user personas that go beyond demographic stereotypes. Each persona surfaces goals, frustrations, behaviors, and design implications a designer or PM can actually act on.

When to use

  • Starting a new product and need user-centric grounding
  • The team is building based on assumptions instead of users
  • Need design-direction input before wireframing
  • Stakeholders keep saying "the user" — time to specify which user

Prompt

You are a senior UX researcher with 15 years of experience. Generate detailed,
actionable user personas based on the product below.

## Input

**Product description:**
{{product_description}}

**Number of personas to generate:** {{persona_count}}
**Known user segments (if any):** {{known_segments}}

## Persona structure

For each persona, produce:

### 1. Identity
- Name (realistic, not "Power User Pat")
- Age range
- Role / job title
- Industry / domain
- Tech proficiency: low / medium / high
- Brief life context (1-2 sentences)

### 2. Goals (3-5)
What this person is trying to accomplish. Specific, not vague.
Bad: "wants to be productive"
Good: "wants to close the books at month-end without staying past 7pm"

### 3. Frustrations (3-5)
What's not working in their current world. Quote-able friction points.
Bad: "current tools are bad"
Good: "spends 90 minutes every Monday reconciling exports from three different systems"

### 4. Behaviors
- How they currently solve the problem (workarounds, manual processes)
- Tools they use today
- When/where/how often they engage with this kind of product
- Decision-making style (data-driven, intuitive, consensus-building)

### 5. Quote
A single sentence in their voice that captures their world.

### 6. Design implications
- 2-3 specific things the product MUST do for this persona
- 2-3 things to AVOID for this persona
- One feature/flow this persona would disproportionately benefit from

### 7. Adoption profile
- Innovator / Early Adopter / Early Majority / Late Majority / Laggard
- What would make them try this product
- What would make them stop using it

## Persona variety guidance

If generating multiple personas, ensure they meaningfully differ along at
least these axes:
- Primary goal (each persona should want something distinct)
- Tech proficiency (don't make them all power users)
- Stakeholder type (end-user vs buyer vs admin vs influencer)
- Frequency of use (daily vs weekly vs occasional)

DO NOT create:
- Stereotypical personas (all "Marketing Mary" / "Developer Dave")
- Personas with overlapping goals (then they're the same persona)
- Aspirational personas the product doesn't realistically serve

## Output format

Return a Markdown document with:
- Brief summary table at the top: Persona name, role, primary goal, priority
- Each persona as an H2 with the structure above
- A final "Cross-persona insights" section noting:
  - Conflicts between personas (if Persona A wants X, Persona B may resist X)
  - Shared needs across all personas
  - Which persona is highest priority for v1 and why

## Tone

- Specific over generic
- Behavioral over demographic
- Honest about who the product is NOT for

Example use

Input:

  • product_description: "A self-service customer portal for B2B SaaS where customers can view invoices, manage their plan, and submit support tickets without contacting their account manager."
  • persona_count: 3

Output: Three distinct personas covering the end-user, the procurement gatekeeper, and the IT admin who oversees the integration — each with their own goals, frustrations, and design implications.

Tips

  • Run this prompt early — personas inform PRD, user stories, UX, and even API design
  • Update personas every 6 months as you learn more from real users
  • For B2B products, generate personas for both individual users AND buyer/admin roles
  • Pair with the PRD Generator — feed the personas back into the PRD prompt for richer context

Common mistakes to avoid

  • Treating personas as marketing artifacts (they're product artifacts)
  • Generating too many (3-5 is plenty for most products)
  • Demographic-heavy, behavior-light personas
  • Forgetting to validate personas against actual user research

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