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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.
The workflow
Go from scattered feedback to a clear next step.
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 and nested replies, choosing the top or newest view that fits the research question.
- 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
Raw feedback becomes useful when it is specific.
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
Give your agent the raw feedback and a useful question.
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.
Pricing
Start free. Pay for what you use, or lock in a flat rate.
Credits for flexible, no-commitment usage. Subscriptions for a fixed monthly rate with built-in savings. Subscriptions+ for teams that want volume pricing at scale.
Free plan
30 free requests
A small test drive to verify the API, inspect real responses, and decide whether you want to stay on credits or move to a subscription.
Pay as you go
$1.99 per 1,000 requests
$0.00199 per request
How credits are counted
One credit = one request. No matter how many results come back — replies, comments, search pages — you pay for the call, not the output size.
Your first successful payment unlocks unlimited API keys on the account, including pay-as-you-go credits.
- No monthly commitment — buy only what you need
- Credits never expire — they stay until you use them
- Same API, same MCP access, same data quality
- ∞ req/min
Credits never expire
Buy once, use whenever. There's no monthly reset, no pressure to hit a quota, no wasted credits at the end of a billing cycle.
No strings attached
No subscription to cancel, no seat minimums, no contract to negotiate. Start, pause, or scale whenever you want.
Full access from credit one
Every endpoint, MCP included, is available on credits. You're not on a limited tier — you get the same data as any subscriber.
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.