/ads-audience

name: Audience Persona Builder
description: Builds 5-7 detailed audience personas from a URL with demographics, psychographics, pain points, buying triggers, platform-specific targeting parameters, persona scoring, and negative audiences

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 ty