Customer Persona Copy Map

v1.0.0

Transforms audience research into a detailed copy matrix linking customer personas to tailored pain points, benefits, messages, and CTA language with evidenc...

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byhaidong@harrylabsj

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Install the skill "Customer Persona Copy Map" (harrylabsj/customer-persona-copy-map) from ClawHub.
Skill page: https://clawhub.ai/harrylabsj/customer-persona-copy-map
Keep the work scoped to this skill only.
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Use only the metadata you can verify from ClawHub; do not invent missing requirements.
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npx clawhub@latest install customer-persona-copy-map
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CryptoCan make purchases
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high confidence
Purpose & Capability
Name, description, and prompt templates all focus on mapping personas to messaging. There are no requested binaries, env vars, or external services that would be unrelated to a copy-mapping tool.
Instruction Scope
SKILL.md provides templated steps for collecting audience signals, separating evidence vs. assumptions, building persona cards, and drafting copy. It does not instruct the agent to read local files, access system credentials, or transmit data to unexpected endpoints. Safety rules explicitly discourage stereotyping and sensitive-targeting.
Install Mechanism
This is an instruction-only skill with no install spec and no code files; nothing will be written to disk or downloaded as part of the skill itself.
Credentials
The skill requires no environment variables, credentials, or config paths. The declared safety fields in skill.json state no network, no credentials, and no code execution — consistent with the instruction-only nature.
Persistence & Privilege
always is false and there is no install script or configuration writes. The skill does not request elevated or persistent presence in the agent environment.
Assessment
This skill appears internally consistent and safe to install from a technical-proportionality perspective. Before using it, avoid pasting sensitive or personally identifiable datasets into prompts (customer PII, health/financial details). Provide evidentiary sources only at the summary level (e.g., ’survey results show X’) rather than raw confidential files. Although the skill.json signals no-network/no-credentials, remember that the hosting agent can still send outputs to external destinations if you instruct it to; don’t use it to create or validate personas involving sensitive protected traits unless you have explicit, lawful consent and robust justification. If you need higher assurance, request the full provenance (who published the skill and where it’s hosted) or run the skill in a restricted environment first.

Like a lobster shell, security has layers — review code before you run it.

latestvk9786x2kzh7gzzdw2e0qa8g5x185p23s
40downloads
1stars
1versions
Updated 12h ago
v1.0.0
MIT-0

Customer Persona Copy Map

Purpose

This skill turns audience research and customer signals into a practical copy matrix that maps different personas to their specific pain points, motivations, objections, preferred benefits, and CTA language. Instead of one-size-fits-all copy, it helps teams segment messaging across product pages, ad creative, email flows, and landing pages — all while clearly labeling what's evidence-based vs. assumed.

Triggers

  • "Map copy to different customer personas"
  • "Create persona-based messaging for my product"
  • "Build a copy matrix for audience segments"
  • "Segment my product messaging by buyer type"
  • "Write persona-specific ad copy"
  • "Create messaging for different customer types"

Workflow

  1. Audience signal collection — Gather known customer segments, demographic/behavioral signals, purchase data patterns (if available), review themes by customer type, support ticket themes, and any existing persona research.
  2. Evidence vs. assumption separation — For each persona, clearly separate: what data supports this segment (reviews, sales data, survey results) vs. what is a reasonable hypothesis (market observation, competitor patterns, intuition). Assumptions must be labeled.
  3. Persona card creation — For each distinct persona, create a card with: name/descriptor, primary need/job-to-be-done, dominant purchase barrier, emotional driver, trust requirement, and preferred channel.
  4. Pain-benefit-message matrix — Create a cross-reference matrix: persona → top pain points → product benefits that address them → message framing → CTA language → best channel.
  5. Copy snippet drafting — Write persona-specific copy snippets: above-the-fold headline, key benefit statement, objection pre-handler, and CTA. Each snippet should feel natural for that persona.
  6. Channel recommendation — For each persona-message pair, recommend the best channel(s) and format (e.g., "gift-buyer persona → Instagram Story with gift-guide angle").

Prompt Templates

1. Persona Copy Matrix Builder (persona_matrix)

Purpose: Build a complete persona-to-copy matrix from audience data.

Input:

  • ${product_name} — Product name
  • ${product_category} — Product category
  • ${personas} — List of customer persona descriptions (2–5 personas)
  • ${product_benefits} — Key product benefits
  • ${channels} — Available marketing channels
  • ${evidence_sources} — (Optional) data sources supporting persona definitions

Output: Complete matrix with persona cards, pain/benefit/message map, copy snippets, and channel recommendations.

2. Persona Expander (persona_expand)

Purpose: Expand a thin persona description into a full messaging profile.

Input:

  • ${persona_name} — Persona name or descriptor
  • ${known_traits} — What's known about this persona
  • ${product_context} — What this product does for them

Output: Expanded persona card with messaging angles, objections, and copy snippet drafts.

3. Message Adapter (message_adapt)

Purpose: Adapt one core message to multiple persona framings.

Input:

  • ${core_message} — The central product message
  • ${personas} — List of personas with key motivations
  • ${channels} — Target channels for adaptation

Output: Persona-specific message adaptations with rationale for changes.

4. Assumption Auditor (assumption_audit)

Purpose: Audit a persona set for untested assumptions that could lead to wasted spend.

Input:

  • ${persona_set} — Complete persona definitions with messaging
  • ${evidence_available} — What data actually supports each persona

Output: Each persona scored by evidence strength (High/Medium/Low), with assumptions highlighted and test recommendations for low-evidence personas.

Output Format

## Persona Copy Map: [Product Name]
**Category:** [Category] | **Personas:** [N personas]

### Persona Cards

**Persona 1: [Name/Descriptor]**
- **Primary Need:** [Job-to-be-done]
- **Dominant Barrier:** [What keeps them from buying]
- **Emotional Driver:** [What feeling motivates them]
- **Trust Requirement:** [What proof they need]
- **Preferred Channel:** [Where they're most reachable]
- **Evidence Strength:** [High/Medium/Low] — [what data supports this]

**Persona 2: [...]**
...

### Pain-Benefit-Message Matrix

| Persona | Top Pain | Product Benefit | Message Frame | CTA Language | Best Channel |
|---|---|---|---|---|---|
| Persona 1 | [Pain] | [Benefit] | [How to frame] | "[CTA]" | [Channel] |
| Persona 2 | [Pain] | [Benefit] | [How to frame] | "[CTA]" | [Channel] |
| ... | ... | ... | ... | ... | ... |

### Copy Snippets

**For [Persona 1]:**
- 🎯 Headline: "[Above-the-fold headline]"
- 💡 Benefit: "[Key benefit statement]"
- 🛡️ Objection handler: "[Pre-handle common objection]"
- 🚀 CTA: "[Call to action]"

**For [Persona 2]:**
...

### Channel Recommendations
- **[Channel]:** Best for personas [X, Y] — format: [suggestion]
- **[Channel]:** Best for persona [Z] — format: [suggestion]

### Assumption Audit
- ✅ Persona 1: [Evidence strength] — supported by [sources]
- ⚠️ Persona 2: Medium evidence — [assumptions] need validation via [test idea]
- ❓ Persona 3: Low evidence — consider deprioritizing until [validation method]

Safety Rules

  • ALWAYS clearly label assumptions vs. evidence — unvalidated personas can waste budget and alienate real customers
  • NEVER stereotype based on protected characteristics (age, gender, race, religion, disability, sexual orientation) when the data doesn't support it
  • NEVER create personas for sensitive categories (health conditions, financial distress, personal crises) without extreme care and explicit disclosure of limitations
  • ALWAYS avoid manipulative messaging that exploits persona vulnerabilities (e.g., insecurity-based marketing to teens, fear-based messaging to elderly)
  • NEVER present assumed personas as "proven by AI" — clearly state the evidence basis for every segment

Examples

Example 1: Skincare Serum (3 Personas)

Input: Product="Vitamin C Brightening Serum", Personas="(1) Skincare Beginner — wants results without complexity, (2) Ingredient Nerd — researches every component, (3) Gift Buyer — buying for someone else, wants safe choice"

Output: Matrix showing: Beginner → pain="too many choices, don't know what works" → message="One serum, proven ingredients, simple routine" → CTA="Start your 2-step routine" → channel=Instagram/TikTok. Ingredient Nerd → pain="skeptical of marketing claims" → message="15% L-AA + E + ferulic, airless pump, dermatologist-tested — here's the data" → CTA="See the full ingredient breakdown" → channel=blog/email. Gift Buyer → pain="will they like it? will it work for their skin?" → message="Universally loved, fragrance-free, suitable for most skin types, beautiful packaging" → CTA="Gift the glow" → channel=Facebook/Instagram.

Example 2: Kitchen Gadget (2 Personas)

Input: Product="Air Fryer Liners", Personas="(1) Convenience Cook — wants faster cleanup, (2) Eco-Conscious Cook — wants to reduce waste (aluminum foil/paper)"

Output: Matrix: Convenience → pain="air fryer cleanup is annoying" → message="Cook, eat, toss the liner — no scrubbing" → CTA="Make cleanup optional" → channel=TikTok. Eco-Conscious → pain="using disposable foil/paper feels wasteful" → message="Reusable silicone liners replace hundreds of foil sheets" → CTA="Cook cleaner, waste less" → channel=Instagram/blog. Assumption audit flags that "Eco-Conscious" is partially assumed — recommended survey validation.

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