Proto Persona

Proto Persona

Purpose

Create an initial, assumption-based persona profile that synthesizes available user delegated-research, market data, and stakeholder knowledge into a working hypothesis about your target user. Use this to align teams early in product development, guide initial design decisions, and identify gaps in understanding that require validation through delegated-research.

This is not a validated persona—it's a "proto" (prototype) persona that evolves as you learn more. Think of it as a structured placeholder that prevents design-by-committee while acknowledging you don't have all the answers yet.

Input

Works best with: The target user or segment you need a working profile for. Also useful: Whatever signal exists — support themes, sales anecdotes, analytics, prior delegated-research — plus the decision the persona will guide.

Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.

Arriving empty-handed? That works too. The skill asks who you think the user is and what you already know, then structures it and flags the assumptions needing validation.

Example invocation: Proto-persona for solo bookkeepers adopting our receipt-scanning app — signal: 30 support tickets and 4 sales call notes.

Key Concepts

What is a Proto-Persona?

A proto-persona is a lightweight, hypothesis-driven persona created from:

• Existing delegated-research: User interviews, surveys, analytics (if available)
• Market data: Industry reports, competitor analysis, demographic trends
• Stakeholder knowledge: Sales, support, and team insights
• Informed assumptions: Best guesses that need validation

Proto vs. Validated Persona

Why Use Proto-Personas?

• Speed: Align teams quickly without waiting for months of delegated-research
• Focus: Provides a shared reference point for "who we're building for"
• Hypothesis framing: Makes assumptions explicit, which can then be validated
• Prevents generic design: "Design for everyone" = design for no one

Anti-Patterns (What This Is NOT)

• Not validated delegated-research: Don't treat it as fact—it's a hypothesis
• Not a replacement for user delegated-research: Use it to guide delegated-research, not avoid it
• Not demographic data alone: Age and location don't explain behavior
• Not permanent: Proto-personas should evolve as you learn

When to Use This

• Early-stage product development (before extensive user delegated-research)
• Kicking off a new feature or pivot
• Aligning stakeholders on target users
• Identifying delegated-research gaps (who do we need to interview?)

When NOT to Use This

• After you've done extensive user delegated-research (create a validated persona instead)
• For mature products with known user segments (you should already have validated personas)
• As a substitute for quantitative data (proto-personas inform delegated-research; delegated-research validates them)

Application

Use template.md for the full fill-in structure.

Step 1: Gather Available Context

Before creating a proto-persona, collect:

• User delegated-research: Interview notes, survey results, support tickets
• Analytics: Usage data, demographics, behavioral patterns
• Market data: Industry reports, competitor user bases
• Stakeholder insights: Sales/support/CS teams who interact with users
• Product context: What problem are you solving? (reference skills/problem-statement/SKILL.md)

If missing context: Don't fabricate—note gaps and plan delegated-research to fill them.

Step 2: Define the Persona's Identity

Name

Give the persona an alliterative, memorable name (makes it easier to reference).

### Name
- [Alliterative name, e.g., "Manager Mike," "Startup Sarah," "Enterprise Emma"]

Quality checks:

• Memorable: Can the team recall it easily?
• Not generic: Avoid "User 1" or "Persona A"

Bio & Demographics

Describe who this person is in the real world.

### Bio & Demographics
- [Age range]
- [Geographic location]
- [Social status (married, single, family, etc.)]
- [Online presence (active on LinkedIn, avoids social media, etc.)]
- [Leisure activities]
- [Career status (job title, industry, seniority)]

Quality checks:

• Behavioral, not just demographic: Don't stop at "30-40 years old, lives in SF"—add "Works remotely, active in Slack communities, juggles 3 side projects"
• Context-relevant: Only include demographics that influence product decisions

Example:

• "35-45 years old, lives in urban areas (NYC, SF, Austin)"
• "Director-level at mid-sized tech companies (50-500 employees)"
• "Active on LinkedIn and Twitter, attends 2-3 conferences per year"
• "Married with young kids, values work-life balance"
• "Plays rec sports on weekends, listens to business podcasts during commute"

Step 3: Capture Their Voice

Quotes

Use real or representative quotes that reveal how they think and speak.

### Quotes
- "[Quote 1 revealing what they say, feel, or think]"
- "[Quote 2 revealing frustrations or motivations]"
- "[Quote 3 revealing attitudes or beliefs]"

Quality checks:

• Authentic: Use real quotes from interviews/support tickets if available
• Revealing: Quotes should expose mindset, not just facts ("I need better tools" is weak; "I'm drowning in manual work and can't focus on strategy" is strong)

Example:

• "I spend 10 hours a week in status meetings that could be emails."
• "I'm tired of tools that promise automation but require a developer to set up."
• "My team expects me to have answers immediately, but I'm constantly searching for data."

Step 4: Document Their Context

Pains

What problems or frustrations does this persona experience? (Reference skills/jobs-to-be-done/SKILL.md for structure.)

### Pains
- [Pain point 1 related to the problem space]
- [Pain point 2 related to the problem space]
- [Pain point 3 related to the problem space]

Quality checks:

• Specific: "Frustrated with tools" is vague; "Spends 3 hours/week manually copying data between tools" is specific
• Related to your product: Focus on pains your product could address

What is This Person Trying to Accomplish?

What behaviors, actions, or outcomes are they pursuing?

### What is This Person Trying to Accomplish?
- [Behavior or outcome 1]
- [Behavior or outcome 2]
- [Behavior or outcome 3]

Quality checks:

• Observable: Can you see this behavior? ("Get promoted" is internal; "Deliver projects 2 weeks ahead of schedule" is observable)
• Outcome-focused: Not tasks ("use dashboards") but results ("make data-driven decisions faster")

Goals

What are their wants, needs, dreams?

### Goals
- [Goal 1: want, need, or dream]
- [Goal 2: want, need, or dream]
- [Goal 3: want, need, or dream]

Quality checks:

• Short-term and long-term: Include tactical goals ("ship feature by Q2") and aspirational goals ("become VP within 3 years")
• Personal and professional: "Spend more time with family" can be as relevant as "increase team productivity"

Step 5: Understand Their Influences

Decision-Making Authority

Do they have the power to buy your solution?

### Attitudes & Influences

- **Decision-Making Authority:** [Yes/No + context (e.g., "Has budget authority up to $10k, needs exec approval above that")]

Quality checks:

• Procurement reality: If they're a user but not a buyer, note who approves the purchase

Decision Influencers

Who influences their decisions?

- **Decision Influencers:** [Who influences this person? (e.g., "Boss, peers in industry Slack channels, analyst reports")]

Quality checks:

• Specific: Not just "their manager"—name the types of influences (peer recommendations, Gartner reports, Twitter threads, etc.)

Beliefs & Attitudes

What beliefs and attitudes shape their decisions?

- **Beliefs & Attitudes:** [Beliefs/attitudes that impact decisions (e.g., "Skeptical of tools that require training," "Values data-driven decision making")]

Quality checks:

• Relevant to adoption: Focus on beliefs that affect whether they'd use your product

Step 6: Validate and Iterate

• Share with the team: Does this persona resonate? Do they recognize this person?
• Identify gaps: What don't we know? (Add "[ASSUMPTION—VALIDATE]" tags where uncertain)
• Plan delegated-research: Use the proto-persona to guide who to interview next
• Evolve it: As you learn, update the proto-persona (or graduate it to a validated persona)

Examples

See examples/sample.md for full proto-persona examples.

Mini example excerpt:

### Name
- Manager Mike

### Quotes
- "I spend more time in status meetings than actually building product."

Common Pitfalls

Pitfall 1: Demographics Without Behavior

Symptom: "28 years old, lives in NYC, has a dog"

Consequence: Demographics don't explain why someone would use your product.

Fix: Add behavioral context: "Works remotely, active in 5 Slack communities, values async communication tools."

Pitfall 2: Treating Proto-Persona as Fact

Symptom: "Manager Mike would never use feature X because he hates complexity"

Consequence: You're treating an assumption as validated delegated-research.

Fix: Add "[ASSUMPTION—VALIDATE]" tags and plan interviews to test hypotheses.

Pitfall 3: Creating 10 Proto-Personas

Symptom: Trying to model every possible user type upfront

Consequence: Analysis paralysis. Teams can't focus on a primary user.

Fix: Start with 1-2 proto-personas (primary + secondary). Add more as you validate and expand.

Pitfall 4: Fabricating Quotes

Symptom: Quotes that sound like marketing copy: "I love products that delight me!"

Consequence: Fake personas lead to fake empathy.

Fix: Use real quotes from interviews, support tickets, or sales calls. If you don't have quotes yet, note "[PLACEHOLDER—NEEDS RESEARCH]."

Pitfall 5: Never Validating

Symptom: Proto-persona created 6 months ago, never updated

Consequence: You're designing for a hypothesis that may be wrong.

Fix: Plan delegated-research sprints to validate key assumptions. Evolve the proto-persona as you learn. Graduate it to a validated persona when confidence is high.

References

Related Skills

• skills/problem-statement/SKILL.md — Persona informs the "I am" section
• skills/jobs-to-be-done/SKILL.md — JTBD informs persona pains/goals
• skills/positioning-statement/SKILL.md — Persona is the "For [target]"
• skills/user-story/SKILL.md — Stories use "As a [persona]"

External Frameworks

• Alan Cooper, The Inmates Are Running the Asylum (1998) — Origin of persona concept
• Jeff Gothelf, Lean UX (2013) — Proto-personas as hypothesis-driven delegated-research tools
• Indi Young, Mental Models (2008) — Behavior-driven persona development

Dean's Work

• Proto-Persona Profile Prompt (inspired by Productside Product Manager's Playbook)

Provenance

• Adapted from prompts/proto-persona-profile.md in the https://github.com/deanpeters/product-manager-prompts repo.

Skill type: Component Suggested filename: proto-persona.md Suggested placement: /skills/components/ Dependencies: References skills/jobs-to-be-done/SKILL.md, skills/problem-statement/SKILL.md Used by: skills/positioning-statement/SKILL.md, skills/user-story/SKILL.md, skills/problem-statement/SKILL.md