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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.
GPT

YouTube Monetization Experiment Planner

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GPT-6-LUNA
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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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