HAMMAD YOUSUF

CHANNEL PROSPECTING // FREE LIVE DEMO

YouTube Prospector Agent

THE PROBLEM

Buying-intent comments on YouTube videos are buried under thousands of generic ones, and creators/brands rarely have time to mine them for leads.

21.8% reply rate

Autonomous outreach personalisation (IBRAHIM production)

PROVEN IN PRODUCTION

BOOK A CALL

No pitch — just a plan.

Give me the video topic — I'll read a thousand comments so you don't, find the viewers quietly asking for help, and draft the low-pressure reply that starts the conversation.

Execution trace — recorded run (this agent's real pipeline)

    • Scanning comment activity on the topic

      ok
    • Filtering generic praise from real questions

      ok
    • Ranking comments by buying intent

      ok
    • Drafting a reply for the top leads

      ok
SHOWCASE DASHBOARD — DEMO DATA · SPEAK OR TYPE ABOVE TO USE YOURS

Comment mining time per video

~25 min manual scroll → ~20 sec

projected

Autonomous outreach personalisation (IBRAHIM production)

21.8% reply rate

real · anonymized

"this is way too much for me to do myself, is there someone who does this for small biz owners?"Explicit outsourcing signalHigh
"great tutorial, very clear!"Praise onlyNone
"do you know anyone who does this in Dubai specifically?"Location + referral requestHigh

Reply draft — top comment

Totally fair — this gets complex fast once you're past basic bookkeeping. Happy to take a quick look at your setup if useful, no pressure either way. Feel free to DM.

WHAT IS YOUTUBE PROSPECTOR AGENT?

An AI YouTube prospector agent scans a video's comment section for viewers signalling genuine buying intent — someone saying a DIY topic is too complex for them, or asking for a local recommendation — ranks those comments by intent, and drafts a low-pressure reply for the top ones, turning a comment thread most brands never read past the first twenty into a lead source.

HOW IT WORKS

YouTube comments on how-to and educational content follow a predictable pattern: most are praise ('great video!') or unrelated tangents, but a consistent minority are viewers who just realised the task is harder than they expected and are implicitly asking whether someone can just do it for them. This agent is trained to recognise that specific pattern — an admission of difficulty paired with a request for a recommendation or a person — over generic engagement.

The reply it drafts deliberately avoids a hard pitch in the comment itself, since a sales pitch in a public comment thread reads poorly to everyone else watching; instead it opens a low-pressure DM invitation, consistent with the low-pressure CTA approach the Cold Outreach Crafter agent uses for email.

Gemini 2.0 FlashStructured JSON outputComment-intent classification prompt
system-prompt.md
You are a YouTube comment-mining analyst for a Dubai services business. Given a video topic/channel niche and an offer, surface the comments most likely to signal genuine buying intent (a specific question about doing this themselves, an 'is this too complex for me' signal, a request for a recommendation), score each, and draft one reply per top comment. Output ONLY a JSON array of typed blocks matching the OutputBlock union — no prose outside the JSON. This demo works from a synthetic sample of illustrative comments, not a live YouTube scrape — never present a comment or commenter as a real, currently-posted one; a production deployment would connect to YouTube's Data API or a compliant scraping layer under the channel owner's own access.

USE CASES

Educational content monetisation

A creator or brand that publishes how-to content mines their own comment sections for viewers who'd rather pay someone than DIY.

Competitor channel mining

Scan comments on a competitor or adjacent creator's tutorial videos for viewers explicitly asking for a service recommendation.

Local-service targeting

Filter specifically for comments mentioning a city or region a service business actually covers, like 'in Dubai specifically'.

Content-to-pipeline feedback loop

Track which video topics generate the most high-intent comments to prioritise future content toward what actually creates leads.

RESULTS & BENCHMARKS

Comment mining time per video

~25 min manual scroll → ~20 sec

projected (modeled)

Autonomous outreach personalisation (IBRAHIM production)

21.8% reply rate

real, anonymized

GET THIS RUNNING ON YOUR BUSINESS

Want YouTube Prospector Agent solving this for you?

This runs in production today, not a mockup. Tell me your case on a free 30-minute call, or hire the whole system for $999/mo.

BOOK A CALL

No pitch — just a plan.

hire the whole system

FAQ

Common questions

What kind of YouTube comment signals real buying intent?

An admission the DIY task is too complex paired with a request for a recommendation or a person to do it — a much stronger signal than praise or generic engagement.

Why doesn't the agent draft a hard pitch as the reply?

A sales pitch in a public comment reads poorly to everyone else in the thread — the agent drafts a low-pressure DM invitation instead, the same approach used across every outreach agent on this site.

Does this work on a channel I don't own?

Yes — the mining logic works on any public video's comments, whether it's your own content, a competitor's, or an adjacent creator's.

Hammad Yousuf

Built by Hammad YousufAI Marketing Automation Engineer, 540K+ YouTube subscribers.

See the production missions these agent patterns run in, or hire the whole system.