customer-psychographic-profiler — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited customer-psychographic-profiler (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
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Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use a marketing planning and audience-research lens. 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.
Use observed audience research and verified product facts. Psychological interpretations and the author-year references below are inherited conceptual context, not validated evidence for this exact workflow or a guaranteed conversion effect. Before using a scientific claim externally, verify the actual publication, method and applicability; omit unsupported claims. This is marketing planning, not clinical diagnosis. Do not infer sensitive traits or exploit vulnerabilities.
Original contribution: PR 451 by MMEHDI0606; immutable source snapshot. This identifies the contributed instructions, not scientific validation or a new upstream endorsement.
Before profiling, establish:
If any of this is missing, ask before proceeding.
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).
Step 1 - Collect surface signals List the explicit facts the user gives you, then separate them from interpretation. Use only observable details first. Planning hypothesis (verify before presenting as research): 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. Planning hypothesis (verify before presenting as research): 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. Planning hypothesis (verify before presenting as research): 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. Planning hypothesis (verify before presenting as research): 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. Planning hypothesis (verify before presenting as research): values-based and identity-based consumer models outperform surface-only segmentation in explaining behavior (Zhang et al., 2025; Lavuri et al., 2023).
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.