# Persona Development

## Purpose
Build detailed, evidence-based profiles of your ideal customers to guide product development, marketing messaging, and sales strategy.

## When to Use
- Defining target customer after initial discovery
- Aligning team on who you're building for
- Creating marketing and sales materials
- Prioritizing features and roadmap
- Training new team members on customer

## Process

### 1. Gather Evidence First

**Personas without evidence are fiction.** Before building personas:

- Conduct 15-20+ customer discovery conversations
- Analyze existing customer data (if available)
- Review support tickets and feedback
- Study competitor customers
- Observe actual user behavior

### 2. Identify Persona Dimensions

Build each persona across three layers:

**Layer 1: Demographics (Who they are)**
- Job title / role
- Company size and type
- Industry / vertical
- Seniority level
- Reporting structure
- Team size (if manages others)
- Geographic location

**Layer 2: Psychographics (How they think)**
- Goals and aspirations
- Frustrations and fears
- How they define success
- What they value
- Risk tolerance
- Decision-making style
- Career motivations

**Layer 3: Behaviors (What they do)**
- Where they get information
- What communities they belong to
- What tools they currently use
- How they evaluate vendors
- Who influences their decisions
- How they spend their day
- What triggers buying

### 3. Use the Persona Template

**Name and Photo:**
Give them a memorable name and a representative photo.

**Quote:**
A one-line statement that captures their worldview.
"I don't have time for tools that don't work immediately."

**Demographics:**
- Title: VP of Marketing
- Company: B2B SaaS, 50-200 employees
- Industry: Technology
- Experience: 8-15 years
- Location: Major metro area

**Goals:**
1. Primary goal (what they're ultimately trying to achieve)
2. Secondary goals (supporting objectives)
3. How they measure success

**Frustrations:**
1. Primary pain point (biggest problem)
2. Secondary pains (related issues)
3. What they've tried that didn't work

**Psychographics:**
- Values: [What matters to them]
- Fears: [What keeps them up at night]
- Motivations: [What drives them]
- Decision style: [How they make choices]

**Behaviors:**
- Information sources: [Where they learn]
- Communities: [Where they gather]
- Tools: [What they currently use]
- Buying process: [How they purchase]

**Objections:**
1. Common objection #1 and how to address
2. Common objection #2 and how to address
3. Deal-breakers (what would disqualify you)

### 4. Validate with Real Data

For each persona attribute, note the evidence:

| Attribute | Claim | Evidence |
|-----------|-------|----------|
| Budget authority | Controls $50K+ | 12/15 interviews |
| Pain intensity | "Critical problem" | 8/15 interviews |
| Uses Slack | Daily communication | Observed in 10/15 |
| Reads newsletter X | Info source | Mentioned by 5/15 |

**Evidence levels:**
- **Strong:** Mentioned by 8+ customers, observed behavior
- **Moderate:** Mentioned by 4-7 customers
- **Weak:** Mentioned by 1-3 customers (needs validation)

### 5. Prioritize Personas

If you have multiple personas, rank them:

| Persona | Pain Intensity | Budget | Reachability | Priority |
|---------|----------------|--------|--------------|----------|
| Marketing VP | High | High | Medium | 1 |
| Sales Manager | High | Low | High | 2 |
| CEO | Medium | High | Low | 3 |

**Focus on one primary persona initially.** Trying to serve multiple personas simultaneously dilutes your value proposition.

### 6. Create the Buying Committee

B2B purchases rarely involve one person. Map the committee:

**User Buyer:** Uses the product daily
- What they care about: Ease of use, saves them time
- How to win them: Demo, trial, workflow fit

**Economic Buyer:** Approves the budget
- What they care about: ROI, risk mitigation
- How to win them: Business case, case studies

**Technical Buyer:** Evaluates fit with stack
- What they care about: Integration, security, compliance
- How to win them: Technical docs, architecture review

**Champion:** Advocates for purchase internally
- What they care about: Making the right choice
- How to win them: Arm them with internal selling materials

### 7. Keep Personas Alive

**Update regularly:**
- After every 10 customer conversations
- After product launches or pivots
- When you see changes in conversion patterns

**Use in decisions:**
- "Would [Persona Name] use this feature?"
- "Where would [Persona Name] hear about us?"
- "What would [Persona Name] object to?"

**Share broadly:**
- Print and post in office
- Reference in meetings
- Include in onboarding docs

### 8. Common Mistakes

**Creating personas without evidence:**
"I think our customer is..." = fiction

**Too many personas too early:**
Start with one, expand when validated

**Generic personas:**
"Marketing professional" is not specific enough

**Outdated personas:**
Never updated after initial creation

**Persona worship:**
Using personas to avoid talking to real customers

### 9. Synthesis

After developing your persona:
- Does this persona match who's actually buying?
- Can you find more of this persona easily?
- Does your product truly solve their primary pain?
- Does your messaging resonate with their worldview?
- What would make this persona a perfect fit for you?

## Example

**Product**: AI-powered content calendar for marketing teams

### Primary Persona: "Marketing Manager Maya"

**Quote:**
"I spend more time planning what to post than actually creating content."

**Photo:** Professional woman, 30s, on laptop in modern office

### Demographics

| Attribute | Detail | Evidence |
|-----------|--------|----------|
| Title | Marketing Manager | 14/20 interviews |
| Company size | 50-200 employees | 12/20 interviews |
| Team size | 2-5 direct reports | 10/20 interviews |
| Industry | B2B SaaS | 11/20 interviews |
| Experience | 5-10 years in marketing | 15/20 interviews |
| Location | US, urban | Observed |

### Psychographics

**Goals:**
1. Build a consistent, high-quality content presence
2. Generate more MQLs from content
3. Get promoted to Director

**Frustrations:**
1. "We're always scrambling to figure out what to post next"
2. "My team spends hours on planning meetings"
3. "I can't prove content ROI to leadership"

**Values:**
- Efficiency over perfection
- Data-driven decisions
- Team collaboration

**Fears:**
- Looking disorganized to leadership
- Falling behind competitors
- Missing opportunities due to poor planning

**Decision style:**
- Researches thoroughly before deciding
- Gets input from team
- Needs to justify spend to VP

### Behaviors

**Information sources:**
- Marketing newsletters (Morning Brew, theSkimm)
- LinkedIn content creators
- Podcasts during commute
- Slack communities (Demand Gen group)

**Current tools:**
- Spreadsheets for content calendar (83%)
- Trello/Asana for task management (65%)
- Hootsuite/Buffer for scheduling (70%)
- Google Analytics for measurement

**Buying process:**
1. Identifies problem through frustration
2. Googles solutions
3. Signs up for free trials
4. Gets team feedback
5. Builds business case for VP

### Objections and Responses

| Objection | Response |
|-----------|----------|
| "We already use spreadsheets" | "Most teams we work with used spreadsheets. They save 5+ hours/week after switching." |
| "I need buy-in from my VP" | "Here's an ROI calculator and case study from similar companies." |
| "What if AI suggestions are off-brand?" | "You train the AI on your brand voice. It learns your style." |

### The Buying Committee

| Role | Person | Care About | Win Them |
|------|--------|------------|----------|
| User Buyer | Maya | Ease of use | Free trial |
| Economic Buyer | VP Marketing | ROI, efficiency | Business case |
| Technical Buyer | Marketing Ops | Integration | Zapier, API docs |
| Champion | Maya | Looking good | Success metrics |

### Using Maya in Decisions

**Product:** "Would Maya understand this feature in 10 seconds?"

**Marketing:** "Where would Maya discover us?"
→ LinkedIn ads to Marketing Manager titles
→ Sponsor marketing podcasts
→ Content in Demand Gen Slack

**Sales:** "What would Maya object to?"
→ Prepare ROI calculator
→ Have case study from similar company ready
→ Offer team trial, not individual

**Insight:** Maya helped the team stop debating features in abstract and start asking "Does Maya need this?" When they added an AI feature, they tested it against Maya's mental model—would she trust AI suggestions? This led to a "human review" workflow that increased adoption.
