YouTube Comment Analyzer & Audience Intelligence

Turn public YouTube comments into a decision-ready audience report in minutes. Add one or more video URLs and get sentiment, recurring themes, unanswered questions, objections, content requests, competitor mentions, evidence quotes, and prioritized next actions—without reading thousands of comments or supplying an external AI key.

Use the results to decide what to publish next, improve an offer, compare campaign reactions, or brief a client with evidence instead of guesswork.

What is YouTube Audience Intelligence?

YouTube Audience Intelligence is a YouTube comment analyzer for creators, agencies, product marketers, course businesses, researchers, and brands. It combines comment collection with structured audience analysis and produces outputs that both people and automations can use.

What you get

• An executive summary of the audience response
• Positive, neutral, and negative sentiment counts and rates
• Recurring themes ranked by number of mentions
• Pain points and purchase or usage objections
• Frequently asked audience questions
• Content, product, and feature requests
• Mentions of competitors, creators, products, or alternatives you choose to track
• Representative source comments for every major finding
• Prioritized actions ranked by estimated impact
• Structured dataset rows plus JSON, Markdown, and standalone HTML reports

No model key or separate OpenAI account is required. Runs can be scheduled, called through the Apify API, or connected to other Apify integrations.

How to analyze YouTube comments

1. Open the Input tab and add one or more public YouTube video URLs.
2. Choose Top comments or Newest first, set a comment limit, and optionally add competitor or alternative names.
3. Click Start. When the run finishes, open Output to inspect the dataset or download REPORT.html, REPORT.md, or OUTPUT as JSON.

For a quick first test, use one public video and request 100 comments. Add several videos when you want to compare reactions across campaigns, creators, launches, or competitors.

YouTube comment analyzer input

{
  "sourceType": "youtube",
  "sourceUrls": [
    { "url": "https://www.youtube.com/watch?v=VIDEO_ID" }
  ],
  "sourceMaxItems": 100,
  "sourceSort": "top",
  "competitorNames": ["Brand A", "Creator B"],
  "maxItems": 5000,
  "evidencePerTheme": 3,
  "outputLanguage": "en"
}

Field	What it controls
sourceUrls	One or more public YouTube video URLs
sourceMaxItems	Maximum comments requested for each video
sourceSort	Top comments or newest comments first
competitorNames	Optional names to detect in comment text
maxItems	Hard limit on comments included in the analysis
evidencePerTheme	Representative quotes retained for each theme
outputLanguage	Recommendation text in English or Simplified Chinese

What YouTube audience data does it return?

The first dataset item is the aggregate summary. The remaining items are normalized comments with sentiment, detected themes, questions, objections, and competitor mentions. A shortened summary item looks like this:

{
  "recordType": "summary",
  "summary": {
    "totalReviews": 842,
    "positive": 503,
    "neutral": 211,
    "negative": 128,
    "positiveRate": 0.5974,
    "negativeRate": 0.152
  },
  "themes": [
    {
      "theme": "pricing",
      "mentions": 146,
      "share": 0.1734,
      "netSentiment": -0.31,
      "evidence": [{ "quote": "Is there a lower-priced plan?" }]
    }
  ],
  "questions": [
    { "topic": "pricing", "mentions": 37 }
  ],
  "objections": [
    { "topic": "pricing", "mentions": 24 }
  ],
  "priorityActions": [
    {
      "rank": 1,
      "action": "Revisit pricing and communicate package value",
      "relatedTheme": "pricing"
    }
  ]
}

The example above illustrates the schema; values depend on the comments collected in your run.

Practical use cases

• Creators: find repeated questions and turn them into future videos, chapters, FAQs, or community posts.
• Agencies: generate an evidence-backed audience brief across several client or competitor videos.
• Product teams: surface feature requests, objections, pain points, and alternative products mentioned by viewers.
• Marketers: identify messages audiences repeat in their own words and compare reactions across campaigns.
• Researchers: export normalized comments and aggregate findings to JSON for downstream analysis.

How much does it cost to analyze YouTube comments?

This Actor uses pay-per-result pricing: $0.00005 per Actor start plus $1.00 per 1,000 output dataset items. A run normally produces one summary item plus one item per analyzed comment.

Comment collection is performed by streamers/youtube-comments-scraper in your Apify account. That source Actor's charge is separate and is shown by Apify before and after the run. Your final cost therefore depends on the requested comment count and the source Actor's current pricing. Start with 100 comments to validate the output before scaling up.

Accuracy, privacy, and limitations

• Only comments available to the public source Actor can be collected; private, disabled, removed, or inaccessible comments are not available.
• Sentiment, themes, questions, and objections are detected with deterministic language rules. They are fast and reproducible, but sarcasm, slang, mixed languages, and highly specialized terminology can require human review.
• Evidence quotes and source URLs are included so important conclusions can be checked against the original comments.
• Do not use the output for high-stakes decisions about individuals. Follow YouTube's terms, Apify's terms, and applicable privacy and data-protection laws.

FAQ

Do I need a YouTube API key or an AI API key?

No. You only need an Apify account. The source Actor handles public comment collection, and this Actor performs the analysis.

Can I analyze several videos in one run?

Yes. Add multiple public video URLs to compare or combine audience reactions. Use maxItems to cap the total number analyzed.

Can I export the report?

Yes. Use the structured dataset or download JSON, Markdown, and standalone HTML reports. You can also call the Actor through the Apify API or schedule recurring runs.

Why did my run return fewer comments than requested?

The video may have fewer accessible comments, comments may be disabled, or the source Actor may not be able to access every thread. Check the run log and reduce the scope to one known-public video when troubleshooting.

More audience and review intelligence tools

• Review Intelligence Analyzer for pasted reviews, existing datasets, Google Maps reviews, and YouTube comments in one workflow.
• Google Maps Review Intelligence for local-business reputation, pain points, and service improvement opportunities.