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audience-research

Analyze YouTube demographics, comments, retention, and engagement to build viewer profiles.

Updated Apr 11, 2026
Search Tags:#analytics#audience#demographics#comments-analysis#viewer-behavior#content-market-fit#viewer-profile
One-click install
npx skills add https://github.com/Jlsiles/Craig---Skills --skill audience-research-jlsiles
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: audience-research
Source: https://github.com/Jlsiles/Craig---Skills/tree/main/youtube/audience-research
Command: npx skills add https://github.com/Jlsiles/Craig---Skills --skill audience-research-jlsiles

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

YouTube creators often struggle to understand what their actual audience wants, leading to content that underperforms because it ignores viewer signals like comments, engagement patterns, and retention. This Skill provides a structured approach to mine audience insights from comments, demographics, and performance data to inform content strategy.

Core Features & Use Cases

  • Audience signal mining: extract questions, intents, and pain points from comments to generate video ideas and titles.
  • Viewer profiling: build richer profiles combining demographics, behavior, and engagement to guide content pillars.
  • Content-market-fit assessment: identify topics with high subscriber conversion and stable retention across similar videos.

Quick Start

Provide a comprehensive audience profile and content plan by analyzing comments, demographics, and retention data for my channel.

Frequently Asked Questions about audience-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze YouTube audience signals to improve my content strategy?▼

Analyzing YouTube audience signals involves extracting viewer intents and pain points from comments, demographics, and retention data to build profiles and actionable content plans. This approach mines engagement patterns to generate video ideas that align with what your actual audience wants.

What is content-market fit and how does it relate to viewer retention?▼

Content-market fit identifies topics with high subscriber conversion and stable retention across similar videos. It assesses whether your content aligns with viewer expectations by analyzing engagement patterns and demographics to ensure long-term audience growth.

Can I generate video ideas from YouTube comments analysis?▼

YouTube comments analysis extracts viewer questions, intents, and pain points to generate targeted video ideas and titles. By mining audience signals from comment sentiment and engagement data, you can create content that directly addresses viewer demands.

How do I build a viewer persona using demographics and engagement data?▼

Building a viewer persona combines demographics, behavior patterns, and engagement metrics to guide content pillars. This profile aggregates audience signals from recent videos to represent your typical viewer and inform targeted content creation.

What is the best way to prioritize a content plan based on audience insights?▼

Prioritizing a content plan based on audience insights uses viewer profiles and content-market fit signals to rank topics. This method identifies high-conversion subjects by analyzing retention and engagement data to deliver concrete, actionable steps for your next videos.

Does this approach work for analyzing viewer behavior across recent YouTube videos?▼

Analyzing viewer behavior across recent YouTube videos requires aggregating demographics, retention, and engagement data to identify performance trends. This process evaluates audience signals from your latest content to build accurate viewer profiles and guide future strategy.

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