What problem does it solve?
Manually sifting through hundreds of raw audience feedback entries (surveys, DMs, call transcripts, spreadsheet data) to identify actual user needs, pain points, and trends is time-consuming and often leads to missed key insights. This skill automates the end-to-end analysis process to surface high-impact, actionable audience intelligence.
Core Features & Use Cases
- Deep Need Clustering: Groups raw audience quotes by underlying user needs and contexts (not just mentioned tools or topics) to uncover what your audience actually wants to achieve.
- Dual Heat Scoring: Ranks needs by both basic popularity (frequency, recency, trend) and business relevance (share of business owners, warm leads, product interest) to prioritize high-impact opportunities.
- Coverage & Gap Analysis: Maps identified needs against your existing content library to spot uncovered gaps and opportunities for new content.
- Segment-Specific Insights: Delivers tailored business insights for key audience segments including business owners, warm leads, and users already interested in your product.
- Use Case: A content creator with 600 survey responses can use this skill to identify their audience's top 3 unmet needs, the business relevance of each, and exactly what content to create next to fill gaps.
Quick Start
Use the audience-analyzer skill to process the attached audience survey CSV file and generate a full prioritized needs report with heat scores, business insights, and content recommendations.