Audience Persona Builder

Skill Purpose

Build 5-7 hyper-detailed audience personas from a business URL. Each persona goes far beyond basic demographics — it maps psychographic profiles, buying triggers, objections, content consumption habits, platform presence, and ready-to-use targeting parameters for Meta, Google, LinkedIn, TikTok, and Pinterest. Includes persona relevance scoring (1-5) and a negative audience section defining who NOT to target. Produces a single, copy-paste-ready deliverable that an ad buyer can immediately use to build campaigns.

When to Use

User runs /ads audience <url>
User asks to build audience personas, customer profiles, or targeting research
Called as a subagent from /ads strategy (the main orchestrator)
User wants to know "who should I target?" for a business
User needs platform-specific targeting parameters for campaign setup

Input Requirements

Required: A business URL to analyze
Optional: Industry context, existing customer data, geographic focus, budget range

How to Execute

Step 1: Business Intelligence Gathering

Fetch the business URL using WebFetch and extract:

Data Point	Where to Find
Business name	Page title, logo, about page
Industry/category	Services offered, product types
Value proposition	Hero section, tagline, about page
Price positioning	Pricing page, product prices, "starting at" language
Geographic focus	Service areas, locations, shipping info
Current customers	Testimonials, case studies, reviews
Product/service types	Product pages, service descriptions
Brand tone	Copy style, imagery, color palette
Trust signals	Certifications, awards, years in business, client logos
Content topics	Blog posts, resources, FAQ sections

Run supplementary searches:

WebSearch: "[Business Name]" reviews
WebSearch: "[Business Name]" customers testimonials
WebSearch: "[Industry]" target audience demographics
WebSearch: "[Industry]" buyer persona research 2025
WebSearch: "[Competitor]" "who buys" OR "target market" OR "customer profile"

Step 2: Industry Audience Intelligence

Based on the detected industry, pull standard audience benchmarks:

SaaS/Software:

Decision makers: CTOs, VPs Engineering, Product Managers, IT Directors
Influencers: Individual contributors who discover tools
Budget holders: CFOs, COOs, department heads
Research behavior: G2 reviews, Product Hunt, Reddit, comparison articles

E-commerce:

Impulse buyers vs. researchers
Price-sensitive vs. quality-focused segments
Brand loyal vs. deal hunters
Social commerce behavior: Instagram shops, TikTok shop, Pinterest

Local Services:

Emergency/urgent need buyers
Planned purchase/project buyers
Referral-driven customers
Neighborhood/community-oriented segments

Agency/Professional Services:

Decision timeline: 30-90 day sales cycles
Committee buyers vs. solo decision makers
Budget-constrained vs. ROI-focused
Relationship-driven vs. results-driven

Creator/Course:

Aspiration-driven buyers
Career changers vs. skill upgraders
DIY vs. guided learning preference
Community seekers vs. content consumers

Step 3: Build Persona Profiles

Build 5-7 personas following this exact structure for each:

Persona Template

### Persona [Number]: [Persona Name] — "[Memorable Tagline]"

**Relevance Score:** [1-5 stars] ★★★★☆
**Revenue Potential:** [Low / Medium / High / Very High]
**Estimated Audience Size:** [Small / Medium / Large]
**Acquisition Difficulty:** [Easy / Moderate / Hard]
**Recommended Priority:** [Primary / Secondary / Tertiary]

---

#### Demographics
| Attribute | Detail |
|---|---|
| Age range | [range] |
| Gender split | [percentage breakdown] |
| Income level | [range and bracket] |
| Education | [level] |
| Job titles | [3-5 specific titles] |
| Company size | [employee range or N/A] |
| Location type | [urban/suburban/rural + specific geos if applicable] |
| Family status | [single/married/parent + relevance] |
| Device usage | [mobile-first / desktop-heavy / multi-device] |

#### Psychographics
| Attribute | Detail |
|---|---|
| Core values | [3-4 values] |
| Aspirations | [what they want to become/achieve] |
| Fears | [what keeps them up at night] |
| Identity | [how they see themselves] |
| Decision style | [analytical/emotional/social proof/authority-driven] |
| Brand affinities | [brands they already buy from] |
| Media consumption | [podcasts, YouTube channels, newsletters, blogs] |
| Social behavior | [lurker/engager/creator + which platforms] |

#### Pain Points (ranked by intensity)
1. **[Pain Point 1]** — [1-2 sentence description of the pain and its impact]
2. **[Pain Point 2]** — [description]
3. **[Pain Point 3]** — [description]
4. **[Pain Point 4]** — [description]
5. **[Pain Point 5]** — [description]

#### Buying Triggers
What makes this persona pull out their wallet RIGHT NOW:
- **Trigger 1:** [specific event or realization]
- **Trigger 2:** [specific event or realization]
- **Trigger 3:** [specific event or realization]
- **Trigger 4:** [specific event or realization]

#### Objections & Hesitations
What stops them from buying:
| Objection | Severity | How to Overcome |
|---|---|---|
| [objection 1] | High/Med/Low | [counter-strategy for ad copy] |
| [objection 2] | High/Med/Low | [counter-strategy] |
| [objection 3] | High/Med/Low | [counter-strategy] |
| [objection 4] | High/Med/Low | [counter-strategy] |

#### Content Consumption Habits
| Platform | Behavior | Content Types They Engage With |
|---|---|---|
| YouTube | [how they use it] | [specific content types] |
| Instagram | [how they use it] | [specific content types] |
| TikTok | [how they use it] | [specific content types] |
| LinkedIn | [how they use it] | [specific content types] |
| Podcasts | [which ones] | [topics] |
| Newsletters | [which ones] | [topics] |
| Reddit | [subreddits] | [discussion types] |
| Google Search | [what they search for] | [query patterns] |

#### Platform Targeting Parameters

**Meta (Facebook/Instagram):**
- Interests: [10-15 specific targetable interests]
- Behaviors: [5-7 behavioral targeting options]
- Lookalike source: [what custom audience to seed from]
- Exclusions: [who to exclude within this targeting]

**Google Ads:**
- Search keywords: [10-15 keywords this persona would search]
- In-market audiences: [Google's in-market segments]
- Affinity audiences: [Google's affinity segments]
- Custom intent keywords: [5-7 high-intent keywords]

**LinkedIn:**
- Job titles: [5-7 exact titles]
- Job functions: [2-3 functions]
- Industries: [3-5 industries]
- Company sizes: [ranges]
- Seniority levels: [levels]
- Skills: [5-7 skills to target]
- Groups: [relevant LinkedIn groups]

**TikTok:**
- Interest categories: [TikTok's interest targeting]
- Behavioral targeting: [video interaction types]
- Creator categories: [types of creators they follow]
- Hashtag targeting: [relevant hashtags]

**Pinterest:**
- Interest targeting: [Pinterest interest categories]
- Keyword targeting: [search terms on Pinterest]
- Actalike audiences: [seed audience description]

#### The Perfect Ad for This Persona
- **Hook angle:** [what opening line would stop their scroll]
- **Emotional trigger:** [the core emotion to tap into]
- **Proof type:** [what evidence convinces them — stats, testimonials, demos, case studies]
- **CTA style:** [soft ask vs. hard ask, what language works]
- **Creative format:** [video/image/carousel + style — UGC, polished, meme, etc.]

Step 4: Persona Scoring Matrix

After building all personas, create a comparison matrix:

## Persona Scoring Matrix

| Persona | Relevance (1-5) | Revenue Potential | Audience Size | Acquisition Cost | Priority |
|---|---|---|---|---|---|
| [Persona 1] | ★★★★★ | Very High | Medium | Moderate | Primary |
| [Persona 2] | ★★★★☆ | High | Large | Easy | Primary |
| [Persona 3] | ★★★★☆ | Medium | Large | Easy | Secondary |
| [Persona 4] | ★★★☆☆ | High | Small | Hard | Secondary |
| [Persona 5] | ★★★☆☆ | Medium | Medium | Moderate | Tertiary |
| [Persona 6] | ★★☆☆☆ | Low | Large | Easy | Tertiary |

Scoring criteria:

Relevance (1-5): How closely this persona matches the business's ideal customer
- 5 = Perfect match, highest conversion probability
- 4 = Strong match, proven buyer profile
- 3 = Moderate match, needs nurturing
- 2 = Weak match, low conversion expected
- 1 = Marginal match, only target if budget allows
Revenue Potential: Expected lifetime value of this persona
Audience Size: How large is this segment on ad platforms
Acquisition Cost: Estimated relative cost to acquire this persona
Priority: Primary (target first), Secondary (expand to), Tertiary (test with remaining budget)

Step 5: Negative Audiences

Define who NOT to target. This section saves ad spend and improves ROAS.

## Negative Audiences — Who NOT to Target

### Hard Exclusions (always exclude)
| Audience | Why Exclude | Platform Exclusion Method |
|---|---|---|
| [audience 1] | [reason — tire kickers, wrong intent, etc.] | [how to exclude on Meta, Google, etc.] |
| [audience 2] | [reason] | [exclusion method] |
| [audience 3] | [reason] | [exclusion method] |
| [audience 4] | [reason] | [exclusion method] |
| [audience 5] | [reason] | [exclusion method] |

### Soft Exclusions (exclude in early campaigns, test later)
| Audience | Why Consider Excluding | When to Test |
|---|---|---|
| [audience 1] | [reason] | [conditions for testing] |
| [audience 2] | [reason] | [conditions] |
| [audience 3] | [reason] | [conditions] |

### Negative Keyword Themes (Google Ads)
- [theme 1]: [list of negative keywords]
- [theme 2]: [list of negative keywords]
- [theme 3]: [list of negative keywords]
- [theme 4]: [list of negative keywords]

### Audience Suppression Lists
- **Existing customers:** Suppress from acquisition campaigns (upload customer email list)
- **Past converters:** Suppress from top-of-funnel (use pixel data)
- **Job seekers:** Exclude "[company name] jobs/careers" searches
- **Competitors' employees:** Exclude unless running competitive conquesting
- **Students/researchers:** Exclude unless product is education-focused

Step 6: Cross-Persona Insights

## Cross-Persona Insights

### Shared Pain Points Across All Personas
1. [pain point that appears in 3+ personas]
2. [pain point that appears in 3+ personas]
3. [pain point that appears in 3+ personas]

### Universal Buying Triggers
1. [trigger that works across most personas]
2. [trigger that works across most personas]

### Platform Priority Ranking
Based on where these personas spend time:
1. **[Platform]** — Reaches [X] of [Y] personas, best for [objective]
2. **[Platform]** — Reaches [X] of [Y] personas, best for [objective]
3. **[Platform]** — Reaches [X] of [Y] personas, best for [objective]
4. **[Platform]** — Reaches [X] of [Y] personas, best for [objective]

### Campaign Structure Recommendation
- **Campaign 1 (Primary):** Target Personas [X, Y] on [Platform] — [objective]
- **Campaign 2 (Secondary):** Target Personas [X, Y] on [Platform] — [objective]
- **Campaign 3 (Testing):** Target Persona [X] on [Platform] — [objective]

### Messaging Theme Matrix
| Theme | Persona 1 | Persona 2 | Persona 3 | Persona 4 | Persona 5 |
|---|---|---|---|---|---|
| [theme 1] | Strong | Moderate | Weak | Strong | Moderate |
| [theme 2] | Weak | Strong | Strong | Moderate | Weak |
| [theme 3] | Moderate | Moderate | Strong | Strong | Strong |

Output Format

Save the complete analysis to ADS-AUDIENCE.md in the current working directory.

File structure:

# Audience Persona Report: [Business Name]
> Generated [date] | Source: [URL]
> Ad Readiness — Audience Clarity Score: [X/100]

## Executive Summary
[3-4 sentences: who the ideal customers are, which platforms to prioritize, key insight]

## Persona 1: [Name]
[full persona template]

## Persona 2: [Name]
[full persona template]

[...continue for all 5-7 personas]

## Persona Scoring Matrix
[comparison table]

## Negative Audiences
[full negative audience section]

## Cross-Persona Insights
[shared insights and recommendations]

## Next Steps
1. Start with Persona [X] on [Platform] — highest relevance + largest audience
2. Build lookalike audiences from [seed source]
3. Run `/ads copy <platform>` to generate ad copy tailored to top personas
4. Run `/ads hooks` to generate scroll-stopping hooks for each persona
5. Set up A/B tests between Persona [X] and Persona [Y] messaging

Quality Checklist

Before delivering the output, verify:

Audience Clarity Score (0-100)

Calculate and report at the top of the file:

Factor	Weight	Scoring
Persona specificity	25%	Generic (0-40) / Detailed (41-70) / Hyper-specific (71-100)
Targeting actionability	25%	Vague (0-40) / Usable (41-70) / Copy-paste ready (71-100)
Pain point depth	20%	Surface-level (0-40) / Researched (41-70) / Customer-voice (71-100)
Platform coverage	15%	1-2 platforms (0-40) / 3-4 platforms (41-70) / 5+ platforms (71-100)
Negative audience quality	15%	Missing (0) / Basic (1-40) / Detailed with methods (41-100)

Composite Score = Weighted average across all factors