Prompt Details
Model
Chat - (gpt-6-luna)
Token size
3,508
Example input
[CHANNEL_PROFILE]: Platform: YouTube Niche: Practical AI tools and productivity Audience: 8,500 subscribers Content: Tool tutorials, comparisons, and workflow videos Publishing: 2 long-form videos and 3 Shorts per week Email list: 1,200 subscribers Current monetization: YouTube advertising only
[VIEWER_SIGNALS]: Viewers repeatedly ask: - Can you share the prompts used in the video? - Which AI tools are worth paying for? - Can you share the complete workflow? - Which tools should a beginner start with? Complete workflow tutorials usually receive more comments than general AI-news videos. There is no digital-product purchase data yet.
[CONTENT_LIBRARY]: 40+ AI tutorials Personal prompt library 8 workflow diagrams Tutorial scripts Tool-comparison notes Email list No paid product No course
[MONETIZATION_GOAL]: Test a monetization method that complements existing educational content and reduces dependence on advertising.
[EXPERIMENT_CONSTRAINTS]: Available time: 5 hours per week. Budget: Under $100. Prefer one-time digital products. Affiliate partnerships are acceptable when relevant. No membership. No full course. Do not make income promises. Test demand before building a large product.
Example output
1. CHANNEL MONETIZATION SNAPSHOT
Channel:
Practical AI education channel
Niche:
AI tools, workflows, and productivity
Audience:
8,500 subscribers
Content formats:
Long-form tutorials and Shorts
Publishing pattern:
2 long-form videos and 3 Shorts per week
Current monetization:
YouTube advertising
Existing assets:
40+ tutorials, prompt library, 8 workflow diagrams, scripts, comparison notes, and 1,200-person email list.
Primary goal:
Add a monetization path that complements existing educational content.
Key constraint:
Five hours per week and no large product build.
2. VIEWER SIGNAL MAP
Signal:
Repeated requests for prompts used in videos
Evidence Type:
Direct signal
Viewer Need:
Reusable implementation material
Viewer Intent:
IMPLEMENT / OBTAIN
Strength:
High relative to supplied evidence
What It Proves:
Viewers explicitly want access to the resource.
What It Does Not Prove:
Willingness to pay.
Signal:
Questions about which AI tools are worth paying for
Evidence Type:
Direct signal
Viewer Need:
Decision support
Viewer Intent:
CHOOSE
Strength:
High
What It Proves:
Tool-selection uncertainty exists.
What It Does Not Prove:
That the audience will use affiliate links.
Signal:
Workflow videos receive more comments than AI-news videos
Evidence Type:
Behavioural signal
Viewer Need:
Practical application
Viewer Intent:
IMPLEMENT
Strength:
Moderate
What It Proves:
Workflow content produces more discussion.
What It Does Not Prove:
Commercial demand.
3. CONTENT INTENT MAP
Content Theme:
Complete AI workflows
Viewer Intent:
IMPLEMENT
Evidence:
Repeated workflow questions and stronger comments
Monetization Relevance:
High
Existing Assets:
Workflow diagrams, prompts, tutorials
Content Theme:
AI tool comparisons
Viewer Intent:
CHOOSE
Evidence:
Repeated questions about paid tools
Monetization Relevance:
Potential affiliate fit
Existing Assets:
Comparison videos and notes
Content Theme:
Beginner AI setup
Viewer Intent:
LEARN / CHOOSE
Evidence:
Direct beginner questions
Monetization Relevance:
Possible entry toolkit
Existing Assets:
Tutorials and prompts
4. MONETIZATION FIT SCORECARD
Path | Viewer Fit | Evidence | Content Fit | Creator Fit | Asset Leverage | Speed to Test | Build Ease | Workload Ease | Trust | Repeatability | Total
Digital Workflow Toolkit | 10 | 9 | 10 | 10 | 10 | 9 | 9 | 9 | 9 | 9 | 94
Selective Affiliates | 9 | 7 | 9 | 9 | 9 | 10 | 10 | 10 | 8 | 8 | 89
Recorded Workshop | 8 | 6 | 8 | 9 | 8 | 6 | 6 | 7 | 9 | 7 | 74
Membership | 6 | 4 | 7 | 7 | 6 | 4 | 4 | 3 | 8 | 8 | 57
5. PRIORITY DECISION
Primary experiment:
AI Workflow Starter Toolkit
Why:
It combines the strongest viewer signals—requests for complete workflows and prompts—with assets that already exist.
Secondary experiment:
Selective affiliate recommendations inside tool-comparison content.
Why:
Viewer questions indicate decision intent, and the test requires relatively little new product creation.
Not now:
Membership.
Why:
It introduces recurring delivery work and conflicts with the stated preferences.
6. AUDIENCE-TO-OFFER HYPOTHESIS
Target viewer:
Beginner-to-intermediate AI user who wants practical implementation.
Observed need:
Access to reusable prompts and complete workflows.
Intent:
IMPLEMENT / OBTAIN
Offer:
AI Workflow Starter Toolkit
Outcome:
Help viewers reproduce selected workflows shown in videos.
Evidence:
Repeated prompt and workflow requests.
Unknowns:
Willingness to pay and preferred toolkit size.
7. MINIMUM VIABLE EXPERIMENT
Experiment:
Test interest in a small 5-workflow toolkit.
Create:
One product preview, landing page, and delivery structure.
Reuse:
Five existing workflow diagrams, associated prompts, and tutorial material.
Do not build:
Course, membership, large prompt library, or software platform.
Distribution:
Relevant videos, email list, and YouTube community content.
Creator effort:
Designed to fit within existing five-hour weekly limit.
Main assumption:
Viewers value organized implementation material enough to take a meaningful commercial action.
8. CONTENT-TO-MONETIZATION MAP
Video topic:
How I turn meeting notes into action items with AI
Viewer intent:
IMPLEMENT
Free value:
Complete workflow demonstration
Monetization connection:
Editable workflow map and prompts
Best placement:
After the workflow has been demonstrated successfully
Soft CTA:
“If you want the reusable workflow map and prompts, they are included in the starter toolkit.”
Avoid:
Leading the video with the offer.
Video topic:
Which AI writing tools are worth paying for?
Viewer intent:
CHOOSE
Free value:
Explain strengths and trade-offs
Monetization connection:
Selective affiliate link if an appropriate programme exists
Best placement:
When discussing a tool the creator can genuinely recommend
Soft CTA:
“If you decide this tool fits your workflow, I’ve included the relevant link below.”
Avoid:
Recommending every tool for affiliate reasons.
[3 additional opportunities]
9. VALIDATION EXPERIMENT CARD
Hypothesis:
Viewers requesting workflows and prompts will show meaningful intent toward a small organized toolkit.
Audience:
Viewers consuming implementation-focused videos.
Offer:
5-workflow starter toolkit.
Test:
Show one full sample plus the contents of the paid version.
Channel:
YouTube and email.
Required assets:
Sample, simple landing page, product concept, CTA.
Primary signal:
Paid early-access behaviour or another meaningful offer action.
Secondary signal:
Waitlist sign-ups and direct questions about contents or availability.
Does not prove demand:
Views, likes, or positive comments alone.
Continue when:
Viewers take actions indicating meaningful intent toward obtaining the complete toolkit.
Revise when:
Interest exists but recurring objections indicate a different format, scope, or price.
Stop when:
The relevant audience repeatedly encounters the offer with little meaningful intent.
10. SIGNAL LADDER
Attention:
Video views and content engagement.
Interest:
Clicks, replies, toolkit questions.
Intent:
Waitlist, pricing-page actions, early-access enquiries.
Payment:
Verified purchases or paid access.
Only the latter stages provide stronger commercial evidence.
11. PRICING TEST DIRECTION
Pricing approach:
Small one-time product.
Testing options:
Compact starter toolkit versus expanded toolkit.
What should influence price:
Number of workflows, quality of assets, usability, update burden, and audience response.
Evidence still needed:
Willingness to pay.
12. PLATFORM / PARTNERSHIP CHECKS
Platform-native monetization:
Advertising is already reported as active.
Any additional YouTube monetization features:
CURRENT PLATFORM POLICY CHECK REQUIRED.
Affiliate availability:
TO VERIFY for specific tools.
Sponsorship readiness:
No sponsor enquiries were supplied; treat sponsorship as unvalidated.
13. 30-DAY EXPERIMENT PLAN
Week 1
Goal:
Select strongest offer hypothesis.
Actions:
Review workflow questions.
Choose five reusable workflows.
Create product scope.
Expected learning:
Whether enough existing material supports a useful small product.
Week 2
Goal:
Build minimum test assets.
Actions:
Prepare one sample.
Create landing page.
Write simple CTA.
Expected learning:
Whether the offer can be explained clearly.
Week 3
Goal:
Run experiment.
Actions:
Integrate offer into relevant tutorial content and email.
Expected learning:
Viewer interest and intent.
Week 4
Goal:
Evaluate.
Actions:
Review clicks, enquiries, waitlist or purchase behaviour.
Decision:
Continue, revise, or deprioritise.
14. RISKS & UNKNOWNS
- Viewers may expect prompts for free.
- Tool-specific material may require updates.
- No willingness-to-pay evidence exists yet.
- Affiliate programme availability is unknown.
15. NEXT EXPERIMENT
Strong:
Complete and release the small toolkit.
Mixed:
Test a narrower workflow-specific pack.
Weak:
Shift toward selective affiliate testing around high-intent comparison content.
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GPT-6-LUNA
Turn your YouTube channel data, viewer questions, content library, and existing assets into focused monetization experiments. Compares monetization paths, identifies the strongest audience-to-offer fit, maps relevant videos to offers, designs a minimum viable test, defines evidence-based decision rules, and creates a practical 30-day experiment plan without inventing demand or promising income.
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Updated 3 days ago
