Common Startup Industry Classifications (by Difficulty/Capital)

Launching a Startup Blindly? A Recipe for Disaster. A Complete Guide to Difficulty and Reality by Sector

● 1. Classification by Technology Level & Entry Barriers

Not all startups require the same level of technological capability. You must realistically assess your stage based on your current technical skills. In my experience, even when founding a Level 3 SaaS startup, I pulled more than a few all-nighters dealing with development issues haha. Simply put, as the level goes up, the entry barrier gets higher, but success brings a monopoly-like status.

Difficulty (Level)	Type	Key Characteristics	Tech Requirements	Representative Sectors & Examples
Level 1 (Low)	Idea / Lifestyle-based	• Low initial capital • Fast execution possible • Highly competitive (Red Ocean)	★☆☆☆☆ Use existing solutions No-code / Low-code	• E-commerce: Smart Store, Purchasing agent, SNS Market • Simple Brokerage: Local errand services, simple matching services • Content: Newsletters, Blogs, Simple YouTube channels
Level 2 (Mid)	Platform / Service (O2O)	• Requires building a two-sided market (Supply-Demand) • Marketing & Ops capabilities are crucial • Securing initial traffic is key	★★★☆☆ App/Web dev essential Server/DB construction	• O2O Platform: Delivery, Lodging, Laundry, Cleaning matching • Community: Vertical (Topic-specific) SNS, Info sharing apps • Edutech: Online lecture sites, Tutoring matching
Level 3 (High)	Tech-based (SaaS/Fintech)	• High development capability required • B2B focused or advanced B2C • Time needed for initial PMF verification	★★★★☆ Advanced SW Engineering Security / Data processing	• SaaS: Collab tools, CRM, HR management, Marketing solutions • Fintech: Easy remittance, Asset management, Robo-advisors • Data: Big Data analytics, Market prediction solutions
Level 4 (Very High)	Deep Tech	• Long R&D period and high costs • Patents & Source technology essential • High potential for J-Curve growth	★★★★★ PhD-level research staff Specialized equipment/facilities	• AI: LLM development, Video/Voice recognition, Autonomous driving algorithms • Bio/Healthcare: New drug development, Digital therapeutics, Medical devices • Hardware/Robotics: Semiconductor Fabless, Industrial robots, Aerospace

---

● 2. Classification by Scale & Capital Intensity

The size of capital is the most realistic measure determining the direction of a startup. Instead of aiming for huge investments from the start, you should set a scale that fits your situation. I also lacked capital initially, so I secured seed money through government support programs. Simply put, it's the process of deciding whether to 'start small with my own money' or 'go big with other people's money (investment)'.

Category	Scale & Capital Characteristics	Team Composition	Growth Goals & Strategy	Sector Examples
Micro Startup (1-Person/Small Scale)	• Capital: 10M ~ 50M KRW (approx. $7k-$35k) • Office: Shared office, WFH • Risk: Low	• 1 Representative • Or utilizing freelancers	• Goal: Livelihood & Securing monthly cash flow • Strategy: Niche market targeting, Rapid monetization	• Knowledge Business (Lectures, eBooks) • Solo-dev Apps • Design Agencies • Small-scale E-commerce
SME Startup (Venture/Small Business)	• Capital: 50M ~ 300M KRW (approx. $35k-$215k) • Funding: Gov't Support (Preliminary/Early), Angel Investment • Risk: Medium	• Co-founders (2-3) • Initial Team (3-5)	• Goal: Stable revenue & Enterprise value increase • Strategy: Expand market share, Series A investment	• Specialized Mall (D2C) • Manufacturing Startup (OEM) • Early-stage Web/App Service • Marketing Agencies
High-Growth Tech Startup (Unicorn Target)	• Capital: 500M ~ Tens/Hundreds of Billions KRW • Funding: VC Series Investment essential • Risk: Very High (High Risk High Return)	• Full C-Level Executives • Specialized Depts • Large-scale Dev Team	• Goal: IPO or M&A • Strategy: Aggressive expansion despite deficits (Blitzscaling)	• Platforms (Coupang, Toss, etc.) • AI/Semiconductor Source Tech • Bio New Drugs • Global Target SaaS

---

● 3. Detailed Classification by Industry Sector (Difficulty/Cost Analysis)

Be careful, as business models and key risks differ completely by industry. As a bio major, let me advise you: the bio sector is like a black hole where time and money vanish endlessly due to regulations and clinical trials. On the other hand, commerce is a battle of marketing efficiency, so you must be sensitive to trends. Simply put, you need to distinguish between 'what I can make well' and 'what I can sell well'.

Category	Sub-Sector	Business Model (BM)	Difficulty	Initial Cost	Remarks (Key Issues)
ICT / SW	SaaS (B2B)	Monthly/Yearly Subscription	High	Mid	Churn Rate management, High difficulty in initial sales
	Platform (B2C)	Commission, Ads	High	High	Solving the 'Chicken and Egg' problem (Securing Supply/Demand simultaneously), Excessive marketing costs
	Game / Ent.	In-app purchases, IP Sales	High	Mid	High uncertainty of success, Very sensitive to trend changes
Mfg / Hardware	General Mfg	Product sales margin	Mid	Mid	Inventory management burden, Securing distribution channels is essential
	IoT / Device	Device sales + Linked Service	High	High	Prototype production (Mockup/Mold) costs, Mass production risks (QC)
	Semiconductor / Materials	Parts supply, Licensing	Very High	Very High	Advanced technology required, Massive facility investment, Long payback period
Bio / Health	New Drug / Bio	Tech Transfer (L/O), Drug Sales	Very High	Very High	Clinical trial costs & Extreme difficulty passing regulations (FDA/KFDA)
	Digital Healthcare	Subscription, Diagnostic Solution	High	High	Medical law review essential, Difficulty in securing medical data
Commerce / Retail	D2C Brand	Direct Mall Product Sales	Mid	Mid	Branding capability is key, Trend of declining performance marketing efficiency
	Fulfillment / Logistics	Logistics handling fees	Mid	High	Warehouse & Delivery infra construction costs, Economies of scale required