$28

Generate a persona avatar

belt app run falai/flux-dev-lora --input '{

"prompt": "professional headshot photograph of a 35-year-old woman, product manager, friendly confident expression, modern office background, natural lighting, business casual attire, realistic portrait",

"width": 1024,

"height": 1024

}'

## Persona Template

┌──────────────────────────────────────────────────────┐

│ [Avatar Photo] │

│ │

│ SARAH CHEN, 34 │

│ Product Manager at a Series B SaaS startup │

│ │

│ "I spend more time making reports than making │

│ decisions." │

│ │

├──────────────────────────────────────────────────────┤

│ DEMOGRAPHICS │ PSYCHOGRAPHICS │

│ Age: 30-38 │ Values: efficiency, data │

│ Income: $120-160K │ Personality: analytical, │

│ Education: BS/MBA │ organized, collaborative │

│ Location: Urban US │ Interests: productivity, │

│ Role: Product/PM │ leadership, AI tools │

├──────────────────────────────────────────────────────┤

│ GOALS │ PAIN POINTS │

│ • Ship features │ • Too many meetings │

│ faster │ • Manual reporting (15 │

│ • Data-driven │ hrs/week) │

│ decisions │ • Stakeholder alignment │

│ • Team alignment │ is slow │

│ • Career growth to │ • Tool sprawl (8+ apps) │

│ Director │ • No single source of │

│ │ truth │

├──────────────────────────────────────────────────────┤

│ CHANNELS │ BUYING TRIGGERS │

│ • LinkedIn (daily) │ • Peer recommendation │

│ • Product Hunt │ • Free trial experience │

│ • Podcasts (commute) │ • Integration with Jira │

│ • Lenny's Newsletter │ • Team plan pricing │

│ • Twitter/X │ • ROI calculator │

└──────────────────────────────────────────────────────┘

## Building a Persona Step-by-Step

### Step 1: Research

Start with data, not assumptions.

Market demographics

belt app run tavily/search-assistant --input '{

"query": "product manager salary demographics 2024 survey report"

}'

Pain points and challenges

belt app run exa/search --input '{

"query": "biggest challenges facing product managers SaaS companies"

}'

Tool usage patterns

belt app run tavily/search-assistant --input '{

"query": "most popular tools product managers use 2024 survey"

}'

Content consumption habits

belt app run exa/answer --input '{

"question": "Where do product managers get their industry news and professional development?"

}'

### Step 2: Demographics

**Use ranges, not exact values.** Personas represent a segment, not one person.

Field
Format
Example

Age range
X-Y
30-38

Income range
$X-$Y
$120,000-$160,000

Education
Common degrees
BS Computer Science, MBA

Location
Region/type
Urban US, major tech hubs

Job title
Role level
Senior PM, Product Lead

Company size
Range
50-500 employees

Industry
Sector
B2B SaaS

### Step 3: Psychographics

What they think, value, and believe.

Category
Questions to Answer

**Values**
What matters most to them professionally?

**Attitudes**
How do they feel about their industry's direction?

**Motivations**
What drives them at work?

**Personality**
Analytical vs intuitive? Leader vs collaborator?

**Interests**
What do they read/watch/listen to professionally?

**Lifestyle**
Work-life balance preference? Remote/hybrid/office?

### Step 4: Goals

What they're trying to achieve (both professional and personal).

Professional:

• Ship features faster with fewer meetings

• Make data-driven decisions (not gut feelings)

• Get promoted to Director of Product within 2 years

• Build a more autonomous product team

Personal:

• Leave work by 6pm more often

• Be seen as a strategic leader, not a ticket manager

• Stay current with industry trends without information overload

### Step 5: Pain Points

**Quantify whenever possible.** Vague pain = vague persona.

❌ "Has trouble with reporting"

✅ "Spends 15 hours per week creating manual reports for 4 different stakeholders"

❌ "Too many tools"

✅ "Uses 8 different tools daily (Jira, Slack, Notion, Figma, Analytics, Sheets, Docs, Email) with no unified view"

❌ "Meetings are a problem"

✅ "Averages 6 hours of meetings per day, leaving only 2 hours for deep work"

### Step 6: Jobs-to-be-Done (JTBD)

Three types of jobs:

Job Type
Description
Example

**Functional**
The task they need to accomplish
"Prioritize the product backlog based on customer impact data"

**Emotional**
How they want to feel
"Feel confident presenting to the exec team"

**Social**
How they want to be perceived
"Be seen as the person who makes data-driven decisions"

### Step 7: Buying Process

Stage
Behavior

**Awareness**
Reads blog posts, sees peer recommendations on LinkedIn

**Consideration**
Compares 3-4 tools, reads G2/Capterra reviews, asks in Slack communities

**Decision**
Requests demo, needs IT/security approval, evaluates team pricing

**Influencers**
Engineering lead, VP of Product, CFO (for budget)

**Objections**
"Will my team actually adopt it?", "Does it integrate with Jira?"

**Trigger event**
New quarter with aggressive goals, new VP demanding better reporting

### Step 8: Generate Avatar

Match demographics: age, gender, ethnicity, professional context

belt app run falai/flux-dev-lora --input '{

"prompt": "professional headshot photograph of a 34-year-old Asian American woman, product manager, warm confident smile, modern tech office background, natural lighting, wearing smart casual blouse, realistic portrait photography, sharp focus",

"width": 1024,

"height": 1024

}'

**Avatar tips:**

- Match the age range, ethnicity representation, and professional context

- Use "professional headshot photograph" for realistic results

- Friendly, approachable expression (not stock-photo-stiff)

- Background suggests their work environment

- Business casual or industry-appropriate attire

## The Anti-Persona

Equally important: who is NOT your customer.

ANTI-PERSONA: "Enterprise Earl"

• CTO at a 5,000+ person enterprise

• Needs SOC 2, HIPAA, on-premise deployment

• 18-month procurement cycles

• Wants white-glove onboarding and dedicated CSM

• WHY NOT: Our product is self-serve SaaS for SMB/mid-market.

Enterprise needs would require 2+ years of product investment.

Anti-personas prevent wasted effort on customers you can't serve.

## Multiple Personas

Most products have 2-4 personas. More than 4 = too many to serve well.

Priority
Persona
Role

**Primary**
The main user and buyer
Who you optimize for

**Secondary**
Influences the buying decision
Who you need to convince

**Tertiary**
Uses the product occasionally
Who you support, not target

## Validation

Personas based on assumptions are fiction. Validate with:

Method
What You Learn

Customer interviews (5-10)
Real language, real pain points

Support ticket analysis
Actual problems, not assumed ones

Analytics data
Actual behavior, not reported behavior

Survey (50+ responses)
Quantified patterns across segments

Sales call recordings
Objections, buying triggers, language

## Common Mistakes

Mistake
Problem
Fix

Based on assumptions
Fiction, not research
Start with data

Too many personas (6+)
Can't serve everyone well
Max 3-4

Vague pain points
Not actionable
Quantify everything

Demographics only
Misses motivations and behavior
Add psychographics, JTBD

Never updated
Becomes outdated
Review quarterly

No anti-persona
Wasted effort on wrong customers
Define who you're NOT for

Single persona for all
Different users have different needs
Primary/secondary/tertiary

## Related Skills

npx skills add inference-sh/skills@web-search

npx skills add inference-sh/skills@ai-image-generation

npx skills add inference-sh/skills@prompt-engineering