Open your smartphone and refresh the ASP dashboard. Yesterday's confirmed reward: 300 yen again.
If you've ever done low-ticket affiliate marketing, you know that small sigh. No matter how many articles you write or how much you post on social media, your earnings hit a ceiling based on your own manual labor. If you stop, the income stops. Before you know it, you're working a job that pays 800 yen an hour, alone in the middle of the night.
Let me be clear: this article doesn't contain a single line about "making 1 million yen with one button." Making 1 million yen a month with high-ticket affiliates isn't a magic trick anyone can pull off in a few months.
That said, imagine this: In the morning, before you even brew your coffee, you open your laptop to find a draft for a new article already finished from the night before. Your X (Twitter) posts are scheduled. A report is waiting for you, listing which articles dropped in ranking and why, along with rewrite suggestions. All you do is decide the direction and give it a final check.
This isn't a dream; it's a typical morning after handing over the work to Codex (OpenAI's autonomous execution AI). This article outlines the exact steps to create that environment for yourself. Use Codex to eliminate over 90% of high-ticket affiliate tasks, calculate the numbers needed for 1 million yen, and put it on autopilot. I've listed about 40 copy-pasteable prompts in order, assuming you're a beginner. Even if you've never touched Codex, you can set up the system by following along.
Why write this so specifically? Simple: there's too much talk about "AI side hustles" and "automation" that stays at an abstract level. People say "Codex is amazing" or "ChatGPT can automate things," but no one writes what to do, in what order, or with which prompts. That's why people can't start, or can't continue.
I'll reveal the structure honestly. High-ticket affiliate marketing is incredibly simple.
You take offers with commissions between 20,000 and 100,000 yen, close 10 to 50 sales a month, and put that system on autopilot. That's it.
In other words, if you build these three things diligently, anyone can replicate it. Codex is the partner that handles almost all of that construction for you.
We will cover 10 chapters: Offer selection, persona and offer design, mass article production, SNS funnels, sales copy AB testing, prompt engineering, expanding capabilities with MCP, full automation with Codex Automations, avoiding pitfalls, and habits to discard.
By the time you finish reading, you'll have both the "blueprint for 1 million yen" and the "copy-paste implementation steps." All you'll need to do is swap in your product names or niches and hit go.
Let's begin.
Chapter 1: Offer Selection—80% of Success is Decided Here
The first chapter is about "what to sell." It's harsh, but if you get this wrong, no matter how hard you work in later chapters, you won't reach 1 million. If you automate a 1,000 yen product perfectly, you need 1,000 sales. With a 30,000 yen high-ticket offer, you only need 33. The work is the same; the only difference is what you chose first.
90% of people choose based on feeling. By choosing based on data, you immediately enter the top 10%.
1. Tier-S Niche Sniper: Filtering Niches on 3 Axes
Survival in high-ticket niches is determined by commission, approval rate, and search demand. Don't just pick "side hustles" or "beauty"—you'll hit a red ocean or a 3% approval rate trap. Let the AI score these.
Prompt:
You are a market analyst for high-ticket affiliate marketing. Please score the following niche candidates on a scale of 1-10 across three axes: ① Average commission (10,000 yen+ = high score) ② Approval rate (50%+ = high score) ③ Balance between monthly search volume and competition density Provide a one-line rationale for each axis, sort by total score, and only keep "candidates" with a total of 24 points or more. Niche candidates: [ ]
2. ASP Cross-Crawl: Comparing the Same Product Across Networks
Commissions and approval rates for the same product can vary by 2x across different ASPs (Affiliate Service Providers). Don't check manually.
Prompt:
For the following product name, cross-reference major ASPs (A8, Moshimo, afb, AccessTrade, ValueCommerce, Cats) and provide a table. Columns: ASP Name / Commission / Approval Conditions / Estimated Approval Rate / Special Commission Negotiation Availability. If the source cannot be confirmed, write "Unknown"; do not fill with guesses. Product Name: [ ]
3. LTV Reverse Calculator: Working Backward from 1 Million Yen
Prompt:
Provide 5 realistic patterns to achieve a monthly sales goal of 1 million yen. For each pattern, create a table showing: ・Assumed commission ・Required conversions ・Required traffic (at 1%/3%/5% conversion rates) ・Assumed number of articles (at 500/1500/3000 monthly PV per article) Finally, rank them by ease of setup for a beginner.
4. Demand-Saturation Index: Visualizing the Sweet Spot
Prompt:
For the following keyword group, score "Demand (0-10)" and "Saturation (0-10)" and calculate the "Demand ÷ Saturation" index. Sort by the highest index and write 3 lines for each of the top 5 explaining why a beginner can rank in 3 months. Keywords: [ ]
Chapter 2: Persona and Offer Design—Targeting One Person Deeply
5. N=1 Persona Generator
Prompt:
Generate one highly detailed, realistic customer for the following niche: ・Name/Age/Gender/Location ・Occupation/Income/Family/Hobbies ・Top 5 recent worries ・3 keywords they search right before buying ・3 reasons they hesitate to pay ・3 triggers that push them to buy No generalities; use specific details. Niche: [ ]
6. Pain-Stack Mapping: 5 Layers of Worry
Prompt:
Structure this persona's worries into 5 layers: ① Surface (what they say out loud) ② Middle (unvoiced frustrations) ③ Deep (root cause) ④ Fear (worst-case scenario if ignored) ⑤ Ideal (what they truly want) Write 3 for each and propose which layer the copy should target with a rationale.
7. Offer-Market Fit Test
Prompt:
Read the following persona and offer info. Score their alignment on 10 items (10 pts each). ・Under 70: Pivot recommended ・70-85: Redesign offer ・85+: Execute immediately Persona: [ ] / Offer: [ ]
8. Counter-Offer Generator: Differentiating from Rivals
Prompt:
Analyze the following rival LP (Landing Page) and extract 3 main selling points. Then, generate a "counter-narrative" for each that can be justified from the opposite angle. Rival LP: [URL or Text]
Chapter 3: Mass Article Production—One Draft a Day, Automatically
9. SERP Reverse Engineering
Prompt:
Analyze the top 10 search results for the following keyword: ① Common heading structures ② Top 5 discussed points ③ 5 missing questions/loopholes not covered anywhere Based on this, propose a unique heading structure (H2x6, H3x3 each) to outrank them. Keyword: [ ]
10. Skeleton-Then-Fill
Prompt:
For the following theme, list the heading skeleton first (H2x5, H3x3 each). Then, treat each H2 as an independent task and flesh it out with 800 words. Finally, integrate them into a finished version, removing redundancies. Theme: [ ]
11. E-E-A-T Injection: Adding Experience and Expertise
Prompt:
Evaluate the following draft for E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). List 3 missing points for each and generate specific sentences (numbers, names, anecdotes) to insert, indicating where they should go. Draft: [ ]
12. Internal Link Web Designer
Prompt:
Design an internal link map using a topic cluster structure for the following URLs. Categorize into Pillar, Cluster, and Satellite articles. List up to 5 links per article with anchor text suggestions. URL List: [ ]
13. Comparative Review Stack
Prompt:
Generate 3 comparative review articles for the following 3 products. Rotate the "main" product in each article while using the others as comparisons. Structure: Intro, Summary, 3-axis comparison table, Who it's for/not for, Conclusion. Product List: [ ]
Chapter 4: SNS Funnels—Automating the X → note → LINE Relay
14. Hook Library Builder
Prompt:
Analyze the following X posts (3%+ engagement) and extract 10 "Hook Syntaxes." Provide a table with: Usage scenario, Expected reaction, and a Fill-in-the-blank template. Post List: [ ]
15. Thread-to-Article Bridge
Prompt:
Read the following X thread and generate 3 CTA patterns to a note article: ① Curiosity-driven, ② Problem-articulation, ③ Benefit-explicit. Max 140 chars each. Thread: [ ]
16. Lead Magnet Generator
Prompt:
Generate 10 lead magnet ideas for the following persona to encourage LINE registration. Include: Name (max 20 chars), Content summary, Estimated conversion rate, and Production time. Persona: [ ]
17. Follow-up DM Script
Prompt:
Generate a 5-message sequence for LINE after registration: 1. Immediate thanks, 2. Empathy story, 3. Comparison, 4. Social proof, 5. Offer. Use a structure that branches based on sticker reactions. Persona: [ ] / Offer: [ ]
Chapter 5: Automated Sales Copy AB Testing
18. Variant Spawner
Prompt:
Read the following LP and generate 5 variants of the "Catchphrase + Sub-copy + CTA button" for the first view. Use different angles: Fear, Gain, Authority, Empathy, Urgency. LP Text: [ ]
19. Objection Handler
Prompt:
List 10 potential objections for the following offer and generate rebuttal text for each. Don't be pushy; acknowledge the worry and resolve it with data or examples (max 200 chars each). Offer: [ ]
20. Urgency Calibrator
Prompt:
Write 3 levels (Low, Mid, High) of urgency/scarcity copy for the following offer. Include expected conversion vs. annoyance levels. Offer: [ ]
21. Story Arc Injector
Prompt:
Generate a story arc for the following persona/offer. Structure: Daily life → Incident → Conflict → Encounter → Turning point → Success. 200 words per stage. Persona: [ ] / Offer: [ ]
Chapter 6: Refining Prompts for Stability
22. Output-First Specification
Prompt:
Fill this template perfectly: Title: [Max 40 chars, include numbers] Intro: [3 sentences on persona worries] Body: [H2x3 + 300 words each] Conclusion: [1 action proposal] CTA: [Max 15 chars] Theme: [ ]
23. Negative Constraints: Removing the "AI Smell"
Prompt:
Create the following. Strict adherence to prohibitions: ① No "It is important to..." or "Regarding..." ② No excessive 3-character kanji compounds ③ No introductory greetings ④ No escaping into bulleted lists only ⑤ No using the same sentence ending 3 times in a row Rewrite if violated. Target: [ ]
24. XML Structured Tagging
Prompt:
I will instruct using the following structure. Respond according to the tags: <goal>Goal</goal> <context>Background</context> <constraints>Prohibitions</constraints> <examples>References</examples> <output_format>Format</output_format>
25. Self-Refine
Prompt:
Perform 3 steps in 1 response for the following topic: ① Write a first draft ② Score it as a harsh editor on Persuasion, Uniqueness, Logic, Readability, and Completeness ③ Write a revised version based on the scores Topic: [ ]
26. Calibrated Confidence Prompting
Prompt:
When answering, append a "Confidence 0-100%" to each claim. Label <50% as "Speculation" and >70% as "Fact" with a one-line reason. Question: [ ]
Chapter 7: Adding Hands and Feet with MCP
27. Firecrawl MCP: Converting Rival LPs to Markdown
Prompt:
Convert the following URL to Markdown using Firecrawl and apply Technique 8 (Counter-Offer Generator) to produce 3 LP proposals. URL: [ ]
28. Supadata MCP: Extracting Elements from Video
Prompt:
Extract the transcript from this video URL and identify 5 "Hook Syntaxes" and 5 "Retention Points." URL: [ ]
29. Memory MCP: Giving Codex Permanent Memory
Prompt:
Register the following in permanent memory: ① Niche [ ], ② Main Persona [ ], ③ Active Offers/Commissions [ ], ④ Prohibited Angles [ ]. Refer to this in all future sessions.
30. Notion/Sheets MCP: Centralizing Revenue Data
Prompt:
Retrieve current month conversions from the Notion DB "Offer Management" and aggregate by ASP/Offer. Identify offers where approval rates have dropped over the last 3 months and propose 3 hypotheses.
Chapter 8: Full Autopilot with Codex Automations
31. Daily Article Drafter
Automation Schedule: Daily 6:00 AM
Task:
- Get keyword from
./keyword-queue/ - Analyze top 10 SERP structure
- Generate 4,000-word draft
- Save as
./drafts/YYYY-MM-DD.md - Notify Slack
32. Daily SNS Cannon
Automation Schedule: Daily 7:00 AM
Task:
- Reference 10 viral posts from
./content-bank/ - Generate 3 X posts for today's theme
- Insert natural CTA to note
- Send to scheduling tool API
- Notify Slack
33. Weekly SERP Watcher
Automation Schedule: Every Monday 9:00 AM
Task:
- Get rankings for all keywords in
./keywords.csv - Extract keywords that dropped 5+ places
- Analyze gaps vs. top articles
- Report rewrite candidates by priority
- Notify Slack
34. Monthly P&L Reporter
Automation Schedule: 1st of every month 8:00 AM
Task:
- Get all data from Notion "Offer Management"
- Aggregate generated/confirmed amounts and approval rates
- Generate MoM/YoY graphs
- Extract 3 highlights, 3 issues, and 3 focus actions
- Save to
./reports/YYYY-MM.mdand notify Slack
35. Failure Detection Loop
Automation Schedule: Every Friday 10:00 AM
Task:
- Get PV/CV data for last 30 days
- Extract articles where PV dropped 30%+ vs. last 90 days
- Summarize hypotheses (SEO/Trend/Competition), 3 fix directions, and effort estimate
- Notify Slack
Chapter 9: High-Ticket Affiliate Pitfalls
36. Compliance Guard (Pharmaceutical/Advertising Laws)
Prompt:
Read the following article and extract all risk expressions regarding Pharmaceutical/Advertising/Commercial Transaction laws. Provide a table with: Law, Risk Level (H/M/L), and Alternative phrasing. Article: [ ]
37. Approval-Rate Optimizer
Prompt:
Evaluate the following article on 5 axes for approval rate risk: ① Accidental click induction, ② Hyperbole, ③ Off-target exposure, ④ Improper AB testing, ⑤ Unclear exit paths. If total score < 30/50, label as "Fix before publishing." Article: [ ]
38. ASP Diversification
Prompt:
Evaluate current offer composition for risk: ① Revenue dependency per offer, ② per ASP, ③ per niche. Calculate impact if the top offer ends and suggest 5 alternatives. Current Status: [ ]
39. Tier Migration Plan
Prompt:
Design a roadmap to migrate from Low (~3k yen) to Mid (3k-15k) to High (15k+) ticket offers. Include: Offer types, Required articles, Validation period, and Criteria to move to the next stage. Persona: [ ] / Niche: [ ]
Chapter 10: 3 Habits to Quit
40. Quit "Thinking after 100 articles"
Find the winning path with 5 articles first, then scale. Use Codex to validate those 5 quickly.
41. Quit "Single-point automation"
If you only automate article generation but do SNS manually, the bottleneck just shifts. Use at least 3 of the Chapter 8 automations together.
42. Quit "Skipping the human final check"
This is the most important. Codex makes fatal mistakes a few times a year. A 30-second visual check prevents compliance violations and typos. Humans must hold the final gate.
Conclusion: 1 Million Yen is "Design," Not "Magic"
We've covered 40 steps. The core idea is simple: minimize human work, maximize Codex work. While you sleep, drafts are written, posts go out, rankings are monitored, and reports are generated. You only judge the direction and check the final gate.
Start today by copy-pasting the LTV Reverse Calculator (Technique 3) prompt into Codex or ChatGPT. See how 1 million yen breaks down into commissions and traffic. Once you see the reality, just follow this guide in order.
Thank you for reading.
For those who read this far
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