| name | icp-persona-builder |
| description | Research a company's ideal customer profiles and build detailed synthetic personas. Identifies 4-6 distinct buyer segments through web research, then creates rich, realistic personas with demographics, motivations, skepticism profiles, decision criteria, and language patterns. Saves personas as a reusable client asset that other skills can reference.
|
| tags | ["research"] |
ICP Persona Builder
Research a company's buyer segments and build detailed synthetic personas that model their ideal customers. These personas become a reusable client asset — once built, any skill can load them to evaluate content, messaging, websites, or campaigns through buyer eyes.
Quick Start
Build ICP personas for [company]. Their site is [url].
With known ICPs:
Build personas for [company]. Their ICPs are: [ICP 1], [ICP 2], [ICP 3].
Inputs
| Input | Required | Source |
|---|
| Company name | Yes | User provides |
| Company URL | Recommended | Helps with research |
| Known ICPs | No | User provides, or discovered via research |
| Client context file | No | clients/<client>/context.md if available |
Process
Phase 1: Company Research
Understand what the company does and who they serve:
- WebFetch their website — homepage, product/solutions pages, pricing, "who it's for" pages
- WebSearch for:
- "[company] customers" / "[company] case studies"
- "[company] reviews" (G2, Capterra, TrustRadius)
- "[company] vs" (comparison searches reveal buyer segments)
- "[company] jobs" (who they're hiring to sell to / support)
- Extract signals:
- What problem do they solve?
- What's their pricing/packaging? (Signals ACV and buyer type)
- What industries/verticals do they serve?
- What company sizes do they target?
- What roles/titles appear in case studies and testimonials?
- What's their go-to-market motion? (Self-serve, sales-led, hybrid)
Phase 2: Identify ICP Segments
From the research, identify 4-6 distinct buyer segments. Each segment should represent a meaningfully different type of buyer — different role, different company profile, or different buying motivation.
For each segment, define:
| Attribute | Description |
|---|
| Segment name | Short label (e.g., "Enterprise IT Leader", "Startup Founder", "Agency Operator") |
| Role/titles | Typical job titles in this segment |
| Company profile | Size, stage, industry, tech stack |
| Core pain point | The #1 problem driving them to look for a solution |
| Buying trigger | What event makes them start searching NOW |
| Decision criteria | What matters most when evaluating (ranked) |
| Sophistication | How well they understand the problem space and solution landscape |
| Alternatives | What else they'd consider (competitors, DIY, status quo) |
| Segment size estimate | Rough sense of how big this segment is for the company (primary, secondary, emerging) |
Segment diversity rules:
- At least one technical buyer (evaluates capabilities, architecture, integrations)
- At least one business buyer (evaluates ROI, outcomes, competitive advantage)
- At least one skeptical profile (has been burned before, hard to convince)
- At least one junior/researcher (doing initial research for a decision-maker)
- Try to cover different company sizes if the company serves multiple tiers
Phase 3: Build Synthetic Personas
For each segment, create a detailed synthetic persona. The persona should feel like a real, specific person — not a marketing abstraction.
Persona structure:
{
"id": "persona-slug",
"name": "Jordan Chen",
"segment": "Enterprise IT Leader",
"title": "VP of Engineering",
"company": {
"type": "Mid-market SaaS company",
"size": "200-500 employees",
"stage": "Series B, scaling fast",
"industry": "Financial services technology"
},
"demographics": {
"experience_years": 12,
"reports_to": "CTO",
"team_size": 35,
"budget_authority": "$50K-200K without board approval"
}
— overpromising triggers skepticism
Phase 4: Save Persona Assets
Save to the client directory as reusable assets:
clients/<client>/personas/personas.json — Machine-readable, all personas in an array:
{
"company": "Acme Corp",
"url": "https://acme.com",
"created": "2026-02-26",
"segment_count": 5,
"personas": [ ... ]
}
clients/<client>/personas/personas.md — Human-readable Markdown with all personas written out in prose form, easy to review and share.
clients/<client>/personas/segments.md — Summary table of all segments with key attributes, useful as a quick reference.
Output Summary
After building, present:
- Segment overview table — All segments with key attributes at a glance
- Persona summaries — 2-3 sentence summary of each persona
- Coverage check — Confirm diversity rules are met (technical, business, skeptical, researcher)
- Next steps — Suggest running
icp-website-review or other skills that can use the personas
Tips
- Research depth matters. Spend real time in Phase 1. The better you understand the company's actual customers, the more realistic the personas. Don't just read the homepage — dig into reviews, case studies, job postings.
- Make personas specific. "Marketing Manager" is too generic. "Sarah, Senior Demand Gen Manager at a 50-person B2B SaaS startup who just lost her SDR team to budget cuts" tells you exactly how she'll evaluate a tool.
- Include the language dimension. How the persona describes their problem is often completely different from how the vendor describes their solution. This gap is where messaging fails.
- Skepticism is the most important trait. Every persona needs a clear skepticism profile. What would make them NOT buy? What's their default assumption about vendors?
- This skill has no code script. It's agent-executed using WebSearch and WebFetch. The structured process above guides the research and persona creation.
Dependencies
- Web search capability (for company and ICP research)
- Web fetch capability (for reading website pages)
- No API keys or paid tools required
