How to Systematically Find Great Startup Ideas?

Hello everyone, today I'd like to share with you how to systematically find promising startup sectors and business ideas.

Recently, I conducted a survey in a community group asking about the biggest pain points in entrepreneurship. The most voted answer was "how to find a good startup project." In reality, when it comes to choosing a startup sector, effort is truly insignificant compared to choice. Choice is a hundred times more important than effort, perhaps even far more than a hundred times.

There's a blogger on Twitter, @levelsio, who has built over 70 projects. Ultimately, only 4 of them are profitable, a mere 5% success rate. However, these 4 projects bring him over $100,000 in monthly income. Data from the US also shows that the failure rate for early-stage software companies within 5 years exceeds 80%. With 700,000 new startups founded each year, only 3% eventually grow into companies employing more than 50 people. Therefore, the overall strategy is quite clear — quickly discover new projects, test them rapidly, and if one doesn't work, swiftly move on to the next.

This article will combine systematic methodology with the expressions of real entrepreneurs. It includes both systematic methods and frameworks, as well as personal experiences and case studies, aiming to make it engaging and actionable for you.

1. Overall Framework: How to Systematically Find Good Startup Ideas

When choosing a startup sector, choice is a hundred times more important than effort.

1. Pain-Point Driven: Start from yourself and those around you to uncover real needs.
2. Technology Driven: Pay attention to technological trends, using new tech to solve old problems.
3. Payment/Cash Flow Driven: Analyze cash flows to discover industries or websites that are already making money.
4. Traffic Driven: Analyze search trends and user interest hotspots to capture market demand.
5. Case Study & Inspiration: Draw inspiration from domestic and international startup communities and product platforms.
6. Social Media/Community Mining: Dive deep into social platforms and comment sections to unearth users' real needs and problems.
7. Signal Radar/Macro Perspective: Continuously capture new opportunities from multi-dimensional signal sources: supply chains, demographics, hiring, patents, regulations, assets, platforms, content, pricing, failure cases, etc.
8. Integrated Methodology & Actionable Advice: Cross-validate from multiple dimensions, rapid prototyping and small-scale validation, continuous tracking and iteration.
9. Appendix: Information Sources & Tool List: Various data sources, platforms, tools, reports, etc.

Next, I'll discuss each method in detail based on practical experience, interspersed with real reflections and case studies.

2. Pain-Point Driven: Starting from Real Needs

1. Core Concept

Good startup projects often stem from unresolved problems faced by oneself or those around you. Pay attention to the difficulties or inefficiencies you, your family, or friends encounter in life, work, or study. These are closest to real needs. Y Combinator also advises entrepreneurs to solve their own or their close circle's pain points, as this makes it easier to validate demand and the entrepreneur is more motivated. Pain points originate from real scenarios, making demand validation easier, and the needs of niche groups often provide clearer entry points.

Many people think entrepreneurship requires grand ideas, but that's not necessarily true. Small problems in daily life, everyday inconveniences, are often the best starting points for a startup.

2. Operational Methods

• Consistently record difficulties or inefficiencies encountered by yourself, family, and friends in life, work, or study.
• Proactively talk to people around you. Ask if they have any frustrations in a specific area, or thoughts like "If only there was a certain product/service..."
• Focus on niche groups (e.g., students, new graduates, the elderly) to more easily find small but promising entry points.
• Conduct in-depth conversations and research. Use the "5 Whys" to repeatedly ask about the root cause of problems. Combine online (WeChat groups, communities) and offline visits, surveys/small-scale research.
• Social Media & Community Mining: Platforms like Reddit, X.com, Zhihu, Douban, Jike, Xiaohongshu, and Douyin comment sections. Look for frequent complaints, questions, and demand posts.
• Product Review & Negative Feedback Analysis: Aggregate negative reviews on App Store/Google Play, e-commerce platforms (Taobao, JD.com). Compare with competitors, focusing on features users commonly complain about.

Sometimes you'll find that the most complained-about areas are often where the most entrepreneurial opportunities lie.

3. Tools & Signal Sources

• Social Media & Comment Sections:
  • Reddit (/r/entrepreneur, /r/productmanagement), X.com (Twitter), Zhihu, Douban groups, Jike topics, Xiaohongshu note comments, Douyin comment sections

4. Advantages

• Pain points originate from real scenarios, making demand validation easier.
• Entrepreneurs themselves are more motivated to solve them.
• Needs of niche groups are easier to find entry points for.

5. Case Studies

• Dropbox's founder developed cloud storage after forgetting his USB drive.
• Discovering user dissatisfaction with fitness apps (lack of personalized plans) on Reddit led to developing a customized fitness guidance tool.
• Negative feedback on specific products/services in Xiaohongshu or Douyin comment sections spurred the creation of improved products.

It's recommended to combine multiple channels and methods, continuously record and validate pain points to build your own "demand library," providing a constant stream of inspiration for future entrepreneurial directions.

3. Technology Driven: Using New Tech to Solve Old Problems

1. Core Concept

Technological progress brings new possibilities, revealing entrepreneurial opportunities that were previously impossible, or previously uneconomical but now viable. Technology-driven ideas often have first-mover advantage and higher barriers to entry.

2. Operational Methods

• Track GitHub open-source projects, tech blogs, tech conferences (e.g., CES, Google I/O, TechCrunch Disrupt). Follow new developments in fields like AI, blockchain, 5G, IoT.
• Combine with traditional industries. Consider whether new technology can improve efficiency or reduce costs.
• Pay attention to API ecosystems, MCP ecosystems, and new business models enabled by cost reductions.
• Monitor changes in infrastructure costs like computing power, storage, and communication.

3. Tools & Signal Sources

• Open-Source Project Tracking:
  • GitHub Trending, Awesome-xx lists, OpenAI Cookbook, Papers with Code, arXiv Sanity
• Tech News & Reports:
  • DeepTech Digest newsletter, Gartner, Forrester, IDC industry reports
• Tech Conferences & Communities:
  • CES, Google I/O, TechCrunch Disrupt, AWS re:Invent
• API & Developer Ecosystems:
  • RapidAPI, APIs.guru

4. Case Studies

• ChatGPT spurred entrepreneurial hotspots like AI writing and customer service chatbots.
• Open-source projects like Stable Diffusion gave rise to AI generation startups.
• Cost reductions made new models like real-time video analysis (e.g., Gemini analyzing video in real-time) and large-scale personalization feasible.
• Recent developments in the AI field, like MCP and new API openings, are excellent entry points.

4. Payment/Cash Flow Driven: Discovering Profitable Industries or Websites Through Cash Flow Analysis

1. Core Concept

Analyzing cash flows to discover industries or websites that are already making money can provide valuable market intelligence for entrepreneurs. Following where money flows makes it easier to earn money. Going where the money is increases the probability of success. If a field has been validated as profitable and money is already being made, it indicates real demand, genuine user willingness to pay, and actual payment capability. This is extremely important.

2. Operational Methods

• Use tools like WhoisMaking.Money to analyze traffic data from payment platforms like Stripe, estimating industry or project revenue.
• Monitor bestseller lists, advertising spend, and fintech data on e-commerce platforms (Amazon, Taobao, JD.com).
• Compare information flow and cash flow data, prioritizing the latter.

3. Tools & Signal Sources

• Payment Traffic Analysis:
  • WhoisMaking.Money, Stripe Payment Insights, Similarweb, Paddle, Chargebee
• E-commerce & Advertising Data:
  • Amazon Bestsellers, Taobao/JD.com rankings, Semrush, App Annie
• B2B SaaS Data:
  • G2, Capterra user reviews & payment data, subscription service reports

4. Case Studies

• Using WhoisMaking.Money to discover a surge in payment traffic for subscription services, then entering that niche market.
• Observing industries with increased advertising spend to identify growth opportunities.
• A sudden sales spike for a product category on an e-commerce platform indicates real demand and strong user willingness to pay.

5. Traffic Driven: Analyzing Search Trends and User Interest Hotspots to Capture Market Demand

1. Core Concept

By analyzing search trends and user interest hotspots, you can capture market demand and discover entrepreneurial opportunities. Traffic-driven approaches help entrepreneurs quickly seize short-term trends or long-term shifts, suitable for content creation or e-commerce.

2. Operational Methods

• Utilize tools like Google Trends, Exploding Topics, Ahrefs, SEMRush to analyze keyword popularity, geographic distribution, and related search queries.
• Monitor trending topics on content platforms like Douyin, Kuaishou, Weibo, Zhihu, Bilibili.
• Track competitor traffic, user retention, promotion costs, etc.

3. Tools & Signal Sources

• Search Trend Analysis:
  • Google Trends, Baidu Index, WeChat Index, Exploding Topics
• SEO & Keyword Tools:
  • Ahrefs, SEMRush, SimilarWeb, App Annie
• Content Platform Trending Lists:
  • Douyin Hot List, Kuaishou Hot Videos, Weibo Hot Search, Zhihu Hot List, Bilibili Hot Videos, Twitter Trending, Reddit Trending

4. Case Studies

• The surge in searches for remote work tools during the pandemic spawned numerous related products.
• The influx of "TikTok refugees" on Xiaohongshu earlier this year was also a major trend.
• Identifying a keyword with a sudden spike in search volume via Google Trends and promptly entering the related market.

6. Case Study & Inspiration: Drawing Ideas from Domestic and International Startup Communities and Product Platforms

1. Core Concept

"Stones from other hills may serve to polish the jade of this one." Drawing inspiration from domestic and international startup communities and product platforms can provide entrepreneurs with valuable startup ideas. Learning from others' experiences can reduce trial-and-error costs and quickly identify viable directions.

2. Methods

• Follow domestic and international product launch platforms and startup communities, analyzing new product features, positioning, and user feedback.
• Study the localization of successful foreign models, leveraging time gaps and cultural adaptation. (e.g., localization of Facebook/Groupon)

3. Tools & Signal Sources

• International Product Discovery Platforms:
  • Product Hunt, Indie Hackers, Hacker News Show, BetaList, BetaPage
• Domestic Product Discovery Platforms:
  • Jike Product Launch, 36Kr, SSPAI, ifanr
• Startup Communities & News:
  • YC Startup School, AngelList, Crunchbase

4. Case Studies

• Domestic entrepreneurs discovered popular tools like Notion on Product Hunt and succeeded by developing localized versions.
• Many domestic products are developed by adapting successful foreign models to local needs.
• Learning from small-team success stories and growth strategies on Indie Hackers.

7. Social Media/Community Mining: Delving into Social Platforms and Comment Sections to Uncover Real User Needs and Problems

1. Core Concept

Delving into social platforms and comment sections to uncover real user needs and problems can provide entrepreneurs with valuable startup ideas. This enables rapid discovery of niche demands.

2. Methods

• Monitor platforms like Reddit, Xiaohongshu, X.com (Twitter), Zhihu, Douban, Jike, etc., searching for user discussions, complaints, and suggestions.
• Monitor e-commerce and app store comment sections, analyzing user positive/negative feedback on products.
• Use keywords like "why isn't there," "is there a kind of," "I want" to filter for needs.

3. Tools & Signal Sources

• Deep Social Platform Mining:
  • Reddit, X.com, Zhihu, Douban, Jike, Xiaohongshu, Douyin
• Vertical Communities & Groups:
  • QQ Groups/WeChat Groups, vertical communities, Discord groups
• Comment Section Analysis:
  • App Store/Google Play, e-commerce platform comment sections

4. Case Studies

• Identifying pain points for fitness apps via Reddit, leading to the development of customized fitness tools.
• Discovering user negative feedback on products/services in Xiaohongshu and Douyin comment sections, spurring improved products.
• Finding numerous users expressing needs like "why isn't there xxx" through keyword searches.

8. Signal Radar / Macro Perspective

1. Core Concept

Continuously capturing new opportunities through multi-dimensional signal sources or slow variables—such as supply chain, demographics, hiring, patents, regulations, assets, platforms, content, pricing, and failure cases—can provide entrepreneurs with valuable startup ideas.

2. Supply Chain Trends / Industry Chain Restructuring

• Monitor structural changes in raw materials, production, logistics, and channels, using signal sources like customs data, industry reports, and tender documents.
• Case: Capacity-sharing platforms, flexible order management SaaS, supply chain finance.

3. Demographic & Social Structure Changes

• Monitor trends like aging populations, declining birth rates, and Generation Z, analyzing data from population censuses and recruitment platforms.
• Case: Elder care tech, pet economy, virtual avatar economy.

4. Reverse Inference from Hiring / Job Demand

• Identify emerging industry opportunities by analyzing new job postings and growing skill demands on recruitment websites.
• Case: AI prompt engineers, i18n localization management.

5. Patent / Research "Funnel"

• Monitor Google Patents, arXiv, and technology transfer offices to find uncommercialized research results.
• Case: New material coatings adapted for e-cigarette heating elements.

6. Regulatory & Compliance Windows

• Monitor new regulations and compliance requirements, analyzing policy documents and law firm newsletters.
• Case: GDPR spurred Cookie consent SaaS, carbon emission audit platforms.

7. Underutilized Asset Redistribution

• Monitor idle assets like parking spaces, warehouses, and GPUs, using government asset catalogs and rental data.
• Case: Serverless GPU, shared automated warehouses.

8. Platform Ecosystem Gaps

• Monitor platform API and plugin ecosystem openings, analyzing Marketplaces, user negative reviews, and Roadmaps.
• Case: Shopify plugins, Notion third-party tools, SaaS connectors.

9. Content / Knowledge Graph Gaps

• Use platforms like Quora, Zhihu, and StackOverflow to capture high-attention questions without answers.
• Case: Knowledge-based SaaS, information subscriptions, courses.

10. Price or Yield Mismatches

• Monitor price differences in energy, commodities, and secondary markets, using electricity price APIs and futures data.
• Case: Intelligent pricing engines, cross-state arbitrage tools.

11. Reverse Inspiration from Failure Cases

• Study post-mortems of failures on YC, IndieHackers, etc., to determine if technical/cost/channel bottlenecks have disappeared.
• Case: The rise of Instacart and Meituan Grocery after Webvan's failure.

It is recommended to establish a "Signal Radar Matrix" in tools like Notion, automatically pulling metrics weekly and cross-validating with core methods.

9. Differences and Mindset Comparison Between Entrepreneurship and Investment

In fact, entrepreneurship and investment are quite similar. Investment strategies can also be broadly divided into two types: top-down and bottom-up. Large investment institutions typically invest by sector, writing investment analysis reports using a top-down macro-analysis approach. They analyze social development trends and market potential from various angles, then evaluate the target, concluding that the sector has significant opportunity and the target has the potential to become a unicorn.

Both investing and entrepreneurship greatly exercise one's cognitive abilities. Their differences lie in:

Entrepreneurship is about discovering a good opportunity and personally bringing it to life. Entrepreneurs invest their own time, energy, connections, and all resources they can mobilize.

Investors discover promising companies and provide tangible financial support. After investing, they offer post-investment services, striving to help the company succeed.

However, their responsibilities are also different. Jack Ma once used an analogy: venture capitalists are the uncles, while the entrepreneurs are the parents of the startup project. The uncle can offer advice and give money for things like milk powder and clothes, but the responsibility of raising the child is yours. VC money is to help you grow and strengthen, not to save you.

10. Comprehensive Methodology & Actionable Advice

1. Multi-Dimensional Cross-Validation

• Compare and score pain points, technical feasibility, and market size in the same table, prioritizing opportunities that score high in all three.

2. Rapid Prototyping & Small-Scale Validation

• Minimum Viable Product (MVP): Implement core functionality in 1-4 weeks, with simple payment/booking.
• Small-scale promotion: Test in WeChat groups, Moments, and communities to gather feedback.

3. Tracking, Iteration & Expansion

• Simultaneously monitor three key drivers: payment flow, search flow, and user feedback.
• After MVP validation, quickly introduce technical/market resources to scale.

4. Actionable Advice

• Combine multiple dimensions to find intersections and increase success probability.
• Continuously learn, dynamically monitor trends, user feedback, and technological developments.
• Establish a "Demand Library" and "Signal Library," regularly reviewing and filtering.

11. Appendix: Information Sources & Tool List

• Technology Trends: GitHub Trending, Papers with Code, arXiv, Gartner, Forrester, IDC, DeepTech Digest
• Payments/Traffic: WhoisMaking.Money, Stripe Payment Insights, Similarweb, App Annie, Paddle, Chargebee
• Traffic Trends: Google Trends, Baidu Index, WeChat Index, Exploding Topics, Ahrefs, SEMRush
• Product Discovery: Product Hunt, Indie Hackers, Jike, 36Kr, SSPAI, ifanr, BetaList, BetaPage
• Social/Community: Reddit, X.com, Zhihu, Douban, Jike, Xiaohongshu, Douyin, QQ Groups/WeChat Groups, Niche Communities
• Supply Chain/Population/Hiring/Patents/Regulations: Panjiva, ImportGenius, UN Comtrade, Flexport, National Bureau of Statistics, LinkedIn, Google Patents, USPTO, China National Intellectual Property Administration, State Council/European Commission/Federal Register
• Assets/Platforms/Content/Prices/Failure Cases: Government Asset Catalogs, Xianyu, Shopify/Notion/Slack Marketplace, Quora, Zhihu, StackOverflow, Real-time Electricity Price APIs, YC/IndieHackers Post-Mortems
• Tool Recommendations: Notion, Excel, Wenjuanxing, WeChat Groups/Communities, Miro, Figma, Zapier, Replit

If there's demand, I could develop this into a product for automated tracking in the future. For example, tracking excellent open-source projects on GitHub, tracking entrepreneurial ideas on Twitter, Xiaohongshu, and Reddit, and tracking great product launches on Product Hunt, etc. If you're interested, please leave a comment.

That's all for my sharing today. Thank you!

References

1. YC Startup Library — Y Combinator's official startup knowledge base. Suggestions like "solving your own or people around you's pain points" align with YC's entrepreneurial philosophy.
2. YC Startup School — YC's free online startup course for systematically learning how to validate a startup idea from scratch.
3. Google Trends — A core tool for the "traffic-driven" method mentioned, used to analyze keyword search popularity and market demand changes.
4. Exploding Topics — A trend discovery tool that can capture topics with rapidly growing search volume before they become mainstream, suitable for finding early-stage entrepreneurial opportunities.