Find what your audience wants next.
Public YouTube comments are a continuous stream of audience language, questions, objections, and ideas. Fetch the conversation from relevant videos, then use the evidence to shape content, product research, and market understanding.
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The workflow
From scattered comments to a content plan.
FetchLayer gives you the public data in a predictable shape. Your code, automation, or AI agent can turn it into an ongoing source of customer insight.
- 01
Select the right videos
Start with your own launches, tutorials, comparison videos, and competitor content where the comments contain useful audience discussion.
- 02
Retrieve the conversation
Use FetchLayer to collect comments, choosing the top or newest view that fits the research question. Load reply threads on demand for deeper discussion.
- 03
Create an evidence-backed brief
Group what viewers ask for and why, then retain representative comments so every recommendation can be checked.
What to surface
What audience language reveals about what to build next.
Questions worth answering
Find the explanations, tutorials, and comparisons viewers repeatedly request in their own words.
Next-content ideas
Turn recurring audience requests into follow-up videos, newsletter sections, FAQs, and product education.
Objections and friction
Surface the concerns that stop a viewer from trying a product, believing a claim, or following the recommended path.
Market language
Learn the phrases audiences use to describe their goals and pain points before writing campaigns or product copy.
Competitor gaps
Read competitor comment sections to see the unanswered needs and requests that their content leaves behind.
Qualitative evidence
Pair quantitative audience metrics with the actual language and reasoning viewers share publicly.
AI-ready input
Point your agent at the conversation, not a survey.
Use FetchLayer through REST or MCP. The important part is keeping the original feedback alongside the summary so your team can inspect the evidence behind every conclusion.
Analyze the comments across these YouTube videos. What outcomes do viewers care about most, what questions remain unanswered, and which three follow-up topics have the strongest evidence?
The research points to a clear next topic: a beginner-friendly comparison with real setup examples. The summary should include the repeated questions and comments that support that recommendation, not just a generic topic list.
Start free. Scale when ready.
Try it free, buy credits as you go, or take a monthly plan when your volume is steady.
Free
$0
30 requests
Enough to call the platforms you care about and read real responses before you pay anything.
- Every platform and endpoint
- REST and MCP
- No credit card
Pay as you go
$1.99
per 1,000
Buy credits when you need them. They stay on your account until you use them.
- Credits never expire
- No monthly commitment
- Same access as subscribers
- ∞ req/min, ∞ API keys
Monthly plan
Starter$25
per month
15,000 requests a month, about 500 a day.
$1.67 per 1,000, $5 less than credits each month
- ∞ req/min, ∞ API keys
1 page fetched is 1 credit
A normal call reads one page. Ask for more pages and each one is one more credit.
The same on every platform
No multiplier for harder targets, and no charge per result returned.
Nothing back, nothing billed
If a request does not return usable data, it costs 0 credits.
Not sure which volume fits?
15 minutes with the founder. Tell us the workload, we tell you what it needs.
Guaranteed throughput on the platform you run on
A dedicated platform from $400/mo, plus $500 for each ~21 req/s. Every other platform on the same key. 99.95% uptime, 24-hour support on Slack or Telegram.
FAQ
Common questions.
Who is YouTube audience research for?
Creators, marketing teams, product teams, researchers, and developers can use public comment data to understand the language, questions, and unmet needs their audience expresses.
Can I research a competitor’s audience?
Yes. Fetch comments from public competitor videos to understand the questions, frustrations, and content gaps visible in their audience conversation.
Can comments help plan new content?
Yes. Look for repeated questions, requested examples, objections, and adjacent topics. The useful output is not only a summary, but the original comment evidence behind the recommendation.
Start with the public feedback.
Retrieve the source data, keep the evidence, and build the feedback workflow your team actually needs.