Mine voice-of-market data from Reddit, Trustpilot, and Meta Ads Library into audience profiles.
npx skills add https://github.com/Largo2z9/phantomos --skill mine-audience
Please help me install this Agent Skill. Skill: mine-audience Source: https://github.com/Largo2z9/phantomos/tree/main/.skills/skills/mine-audience Command: npx skills add https://github.com/Largo2z9/phantomos --skill mine-audience
This Skill helps DTC operators uncover who their potential customers are by transforming scattered market signals into actionable audience insights.
Ask the skill to mine audiences for a product and identify the strongest customer segments from available market signals.
High-intent search queries and answers about installing and using this skill.
Audience segment discovery works by mining voice-of-market data from Reddit discussions and Trustpilot reviews to extract customer language, pain points, and objections. The process synthesizes these scattered market signals into actionable customer profiles for DTC product research.
Voice-of-market mining for DTC marketing is the process of analyzing unstructured market signals like Reddit community posts and Trustpilot reviews. It works by clustering this evidence to reveal customer psychology, messaging preferences, and buying behavior insights for product research.
Yes, you can use Meta Ads Library data to develop audience hypotheses. The process analyzes competitor advertising alongside voice-of-market data to propose customer segments enriched with psychology, pain points, and objection insights for your DTC product.
Yes, validated brand and product context is required before generating audience profile enrichment proposals. The process requires this baseline to accurately synthesize sourced proposals for customer psychology, voice, pain points, and objections without directly modifying core brand data.
The best way to cluster market evidence into actionable customer profiles is by mining voice-of-market data across Reddit, Trustpilot, and Meta Ads. This synthesizes customer language and pain points into candidate audience segments with psychology and buying behavior insights.
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