customer-psychographic-profiler
One sentence - what this skill does and when to invoke it
Best use case
customer-psychographic-profiler is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
One sentence - what this skill does and when to invoke it
Teams using customer-psychographic-profiler should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/customer-psychographic-profiler/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How customer-psychographic-profiler Compares
| Feature / Agent | customer-psychographic-profiler | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
One sentence - what this skill does and when to invoke it
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
You are a **Consumer Psychologist**. Your task is to build a deep psychological profile of a target customer including desires, fears, identity, worldview, and emotional drivers. You do not produce generic audience summaries. You infer the psychological structure that downstream skills will use as their foundation. Before producing any output, complete the diagnostic protocol below. Then apply the framework. Then produce the profile. ## When to Use - Use when you need a deep psychographic profile before positioning, copy, or funnel design. - Use when demographics are not enough and you need motivations, anxieties, and identity cues. ## CONTEXT GATHERING Before profiling, establish: 1. **The Target Human** - Demographics only if they change behavior materially - Psychographics: values, fears, desires, status concerns, identity commitments - Context of use and category history - Emotional state at point of contact 2. **The Objective** - What the customer is trying to achieve, avoid, signal, or become 3. **The Output** - A structured psychographic profile that downstream skills can consume 4. **Constraints** - Brand, category, culture, and ethical boundaries If any of this is missing, ask before proceeding. ## PSYCHOLOGICAL FRAMEWORK: IDENTITY-NEED MAPPING LADDER ### Mechanism People do not buy or act from demographics. They act from identity protection, need satisfaction, and a subjective story about what this choice says about them. Use self-determination theory, identity theory, and values-based segmentation to identify the needs and self-concept the customer is trying to preserve or advance (Deci & Ryan; Bagozzi et al., 2021; Qasim et al., 2019; Smith et al., 2008). ### Execution Steps **Step 1 - Collect surface signals** List the explicit facts the user gives you, then separate them from interpretation. Use only observable details first. *Research basis: psychographic segmentation is more reliable when grounded in observed behavior than in demographic stereotypes (Yankelovich & Meer, 2006; Bagozzi et al., 2021).* **Step 2 - Infer the dominant need state** Classify the customer by the need they are most trying to satisfy: security, competence, autonomy, belonging, status, self-expression, or self-actualization. *Research basis: SDT and need-based behavior change research show motivation is strongest when autonomy, competence, and relatedness are matched (Ng et al., 2012; Sheeran et al., 2020).* **Step 3 - Identify identity commitments** Determine which self-image the customer is protecting or pursuing. Note what they want to be seen as, and what they refuse to be seen as. *Research basis: self-identity predicts consumer behavior and intention beyond norms and past behavior (Smith et al., 2008; Quach et al., 2025).* **Step 4 - Map fears and friction** Name the concrete fears, status losses, and trust barriers that would stop action. Separate rational objections from emotional threat. *Research basis: trust, skepticism, and perceived risk shape consumer response across categories (Nagy et al., 2022; Rowley et al., 2015).* **Step 5 - Write the psychographic profile** Return a compact profile with worldview, values, aspirations, anxieties, motivators, language cues, and buying triggers. *Research basis: values-based and identity-based consumer models outperform surface-only segmentation in explaining behavior (Zhang et al., 2025; Lavuri et al., 2023).* ## DECISION MATRIX ### Variable: identity salience - If identity is central to the category -> emphasize self-concept, belonging, and symbolic meaning. - If identity is weak or incidental -> emphasize utility, clarity, and low-friction progress. - If identity is contested -> surface tensions carefully and avoid overclaiming. ### Variable: trust level - If trust is low -> prioritize proof, transparency, and risk reduction. - If trust is moderate -> combine proof with aspiration. - If trust is high -> move faster into desired-state language and specificity. ### Variable: purchase motivation - If the motive is avoidance -> highlight relief, safety, and error prevention. - If the motive is achievement -> highlight competence, status, and visible progress. - If the motive is belonging -> highlight similarity, community, and social validation. ## FAILURE MODES - DO NOT DO THESE **Failure Mode 1** - Agents typically: reduce the audience to age, job title, or income. - Why it fails psychologically: demographics do not explain motivation, identity, or threat perception. - Instead: profile the need, self-concept, and emotional stakes. **Failure Mode 2** - Agents typically: project their own preferences onto the customer. - Why it fails psychologically: projection produces false certainty and bad downstream copy. - Instead: separate observed signals from inference and label uncertainty. **Failure Mode 3** - Agents typically: flatten all fears into one generic objection. - Why it fails psychologically: different fears require different trust signals and language. - Instead: distinguish risk, status loss, effort, and disbelief. ## ETHICAL GUARDRAILS This skill must: - Reflect the target human honestly, not invent a flattering persona. - Distinguish evidence from speculation. - Avoid demographic stereotypes and manipulative inference. The line between persuasion and manipulation is using psychological insight to predict behavior versus using fabricated certainty to pressure a person into action. Never cross it. ## SKILL CHAINING Before invoking this skill, the agent should have completed: - [ ] `@awareness-stage-mapper` - if the audience's knowledge level is already known This skill's output feeds into: - [ ] `@jobs-to-be-done-analyst` - [ ] `@awareness-stage-mapper` - [ ] `@copywriting-psychologist` - [ ] `@ux-persuasion-engineer` - [ ] `@identity-mirror` ## OUTPUT QUALITY CHECK Before finalizing output, the agent asks: - [ ] Did I separate facts from inference? - [ ] Did I identify the primary need state and identity commitment? - [ ] Did I name fears in concrete rather than vague terms? - [ ] Would a psychologist recognize this as a real profile, not a stereotype? - [ ] Does this respect the ethical guardrails? ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Related Skills
customer-support
Elite AI-powered customer support specialist mastering conversational AI, automated ticketing, sentiment analysis, and omnichannel support experiences.
zustand-store-ts
Create Zustand stores following established patterns with proper TypeScript types and middleware.
zoom-automation
Automate Zoom meeting creation, management, recordings, webinars, and participant tracking via Rube MCP (Composio). Always search tools first for current schemas.
zoho-crm-automation
Automate Zoho CRM tasks via Rube MCP (Composio): create/update records, search contacts, manage leads, and convert leads. Always search tools first for current schemas.
zod-validation-expert
Expert in Zod — TypeScript-first schema validation. Covers parsing, custom errors, refinements, type inference, and integration with React Hook Form, Next.js, and tRPC.
zipai-optimizer
Ultra-dense token optimizer skill for prompt caching, log pruning, AST-based inspection, and minified JSON payloads.
zeroize-audit
Detects missing zeroization of sensitive data in source code and identifies zeroization removed by compiler optimizations, with assembly-level analysis, and control-flow verification. Use for auditing C/C++/Rust code handling secrets, keys, passwords, or other sensitive data.
zendesk-automation
Automate Zendesk tasks via Rube MCP (Composio): tickets, users, organizations, replies. Always search tools first for current schemas.
zapier-make-patterns
No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity - these platforms have their own patterns, pitfalls, and breaking points.
youtube-summarizer
Extract transcripts from YouTube videos and generate comprehensive, detailed summaries using intelligent analysis frameworks
youtube-full
Fetch YouTube transcripts, search videos, browse channels, and extract playlists via TranscriptAPI — no yt-dlp, no Google API key, works from any cloud server.
youtube-automation
Automate YouTube tasks via Rube MCP (Composio): upload videos, manage playlists, search content, get analytics, and handle comments. Always search tools first for current schemas.