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AI Executive Industry Report Deep-Read Matrix | Knowledge Planet Subscription Monthly Revenue of 8,000

Workflow: Every morning at 7:00, Feedly and RSS subscription sources are used to automatically capture the previous day's brokerag

AGENT

Key Fields

FIELD STAMPS

IndustryEducation / Knowledge

RegionChina（中国大陆）

ScaleSME

ChannelOnline

🔧 Workflow

Every morning at 7:00, Feedly and RSS subscription sources are used to automatically capture the previous day's brokerage research reports, tech media AI columns, and industry white papers. At the same time, n8n is used to automatically filter out generalities without ROI data. Subsequently, the DeepSeek and Claude dual models are called to generate decision summaries within 300 words, marking core data, applicable industries, and actionable decision-making suggestions. Manual work only requires 30 minutes to review the summary content, correct data deviations, and simultaneously publish them to 知识星球 and the paid WeChat group. Every Saturday night, a 1-hour live stream is held to dissect the implementation scenarios of a major report and answer user questions.

🛠 Setup Requirements

Building this system requires no programming background. The RSS crawling and automatic filtering modules of n8n have ready-made templates, which can be directly imported and configured to complete automatic collection. If you are unwilling to use automated tools, you can also manually spend 10 minutes a day filtering report sources and then use AI to generate summaries, increasing the time cost by only half an hour. Technical capability only requires mastering basic large model prompt writing, clearly informing AI of the core dimensions that need to be extracted. The overall construction cycle is about 2 weeks. The first week fixes the report sources and publishing rules, and the second week trial operates to adjust the content direction.

🧰 Toolchain

🔧 Feedly
🔧 DeepSeek API
🔧 Claude
🔧 n8n
🔧 知识星球
🔧 Notion

💰 Revenue

Average monthly revenue is about 8,000 RMB: Calculated based on the annual fee of 199 RMB for 知识星球, after 3 months of stable operation, it can usually accumulate 500 paid members, with an annual revenue of about 100,000 RMB, translating to an average monthly revenue of 8,300 RMB. If expanding enterprise-end customized interpretation services, a single customized report charges 2,000 to 5,000 RMB. Taking 3 orders per month can increase revenue by an additional 6,000 to 15,000 RMB, and the overall monthly revenue can be stably maintained above 12,000 RMB.

💸 Cost

Average monthly cost is about 500 RMB: The annual fee of the 知识星球 platform translates to an average of about 80 RMB per month, the large model API monthly fee is around 150 RMB, and research reports from public channels can be obtained at zero cost. If internal paid research reports need to be purchased, it is a maximum of 300 RMB per month, and the initial one-time investment is only about 1,000 RMB to start.

⏱ Time Investment

Investing 2 to 2.5 hours per day, of which 1 hour in the morning is spent on report screening, AI summary generation, and publishing, half an hour at night is spent replying to user questions, and 1 hour is invested every Saturday to do deep report analysis live streams. The overall time investment is controllable and does not affect the main business.

🚀 Getting Started

Step 1: Register a 知识星球 account, determine the vertical niche direction, and prioritize tracks with high executive attention such as AI+manufacturing and AI+finance. Step 2: Fix 3 core report sources, covering top brokerage research reports, AI vertical media, and industry white papers. For 7 consecutive days, use AI to generate summaries and publish them to Moments and free AI industry communication groups, counting the number of users who actively inquire about deep content. Step 3: When accumulating more than 30 users with a clear willingness to pay, officially launch 知识星球, use the free content of the first 7 days as experience materials, and set an early bird price to attract the first batch of users.

🔑 Keys to Success

✅ Report screening standards: Prioritize reports containing specific ROI data, implementation scenarios, and decision-making suggestions, and exclude empty content with grand narratives
✅ Manual review mechanism: AI only generates the first draft, and finally, humans supplement the industry background and decision-making implications to avoid data errors caused by AI hallucinations
✅ Fixed publishing frequency: Publish at the same time every morning to form user reading habits and improve retention rate
✅ Precise title strategy: Each summary title must include specific industries and ROI data, such as '2026 AI Customer Service Track Report: 3 Paths for Enterprises to Reduce Costs by 35%'. The click-through rate is more than 3 times higher than generic titles
✅ Private domain linkage operation: Synchronize each summary to the paid WeChat group, guide user discussions, and improve community activity and renewal rates

⚠️ 风险

⚠️ Copyright risk: Only original interpretations and summaries of the report's core data can be published, and the full text of the report must not be forwarded, otherwise it may be complained about and taken down or even bear infringement liability
⚠️ Homogenization risk: If you only do report translation without providing original decision-making judgments, paid users will churn to free AI tools, failing to form a paid barrier
⚠️ Platform rule risk: If the content is judged to be unauthorized reproduction of the report's core content, the content may be taken down or even banned by 知识星球. All content is required to be original interpretations, citing only public data

📌 Real Cases

📌 知识星球 community 'AI Industry Frontier Deep Reading', operated by a former top brokerage analyst, with an annual fee of 299 RMB, currently has 1,280 paid members, annual subscription revenue exceeding 380,000 RMB, users are mainly middle and senior management of internet companies, investors, and entrepreneurs, and the renewal rate exceeds 60%
📌 Xiaohongshu account 'Report Brother', updates 1 AI industry report summary every day, with 120,000 followers. The paid community channeled to the private domain has an annual fee of 199 RMB, currently has 890 members, average monthly revenue of 14,000 RMB, and content focuses on the interpretation of implementation reports of AI + real economy
📌 The original candidate case '95% of AI projects failed, but this position's salary rose by 800% in nine months', Fan Bing's 'Frontline Deployment Engineer' interpretation article, gained 100k+ reads after publication, channeled over 200 executive users to the private domain, paid conversion rate reached 15%, a single piece of content brought in direct revenue of over 6,000 RMB, and subsequently derived orders for corporate internal training

Sources