# Proto Persona

> Create a proto-persona from current research, market signals, and team knowledge. Use when you need a working customer profile before deeper validation.

- Skill: `ninjasln-labs/proto-persona` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add ninjasln-labs/proto-persona`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ninjasln-labs/proto-persona/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: NinjaSln-labs (https://skillmd.com/u/ninjasln-labs)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ninjasln-labs/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
| Proto-Persona | Validated Persona |
|---------------|-------------------|
| Created in hours/days | Created over weeks/months |
| Based on assumptions + limited delegated-research | Based on extensive user delegated-research |
| Used to align teams early | Used to guide detailed design |
| Evolves rapidly | Stable over time |
| Good enough to start | High confidence |

### 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).

```markdown
### 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.

```markdown
### 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.

```markdown
### 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.)

```markdown
### 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?

```markdown
### 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?

```markdown
### 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?

```markdown
### 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?

```markdown
- **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?

```markdown
- **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:

```markdown
### 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`