Business Feasibility Research

Markdown
# Business Idea Analysis: [Business Name]

• Concept: Brief description
• Market Size: $X billion market
• Feasibility Score: 7/10
• Key Insight: Primary finding that drives recommendation

Target Market

• Demographics
• Size and growth rate
• Pain points addressed

Competition

• Direct competitors (3-5)
• Indirect competitors
• Market gaps identified

• Technical: Implementation complexity
• Financial: Startup costs and revenue model
• Market: Demand validation
• Operational: Resource requirements

• Go/No-go decision with rationale
• Next steps if proceeding
• Risk mitigation strategies

Research Process:

• Define business concept clearly
• Identify target market and size
• Map competitive landscape
• Analyze technical requirements
• Assess financial viability
• Evaluate market demand signals
• Score feasibility across dimensions
• Synthesize findings into actionable insights

Research Dimensions

1. Market Research

   • Industry size and growth trends
   • Target customer segments
   • Pricing benchmarks
   • Regulatory environment

2. Competitive Analysis

   • Direct and indirect competitors
   • Market positioning gaps
   • Competitive advantages/disadvantages
   • Barrier to entry assessment

3. Technical Feasibility

   • Implementation complexity
   • Technology requirements
   • Skill/resource availability
   • Development timeline

4. Financial Viability

   • Startup capital requirements
   • Revenue model validation
   • Unit economics
   • Break-even analysis

Example 1: Input: "AI-powered meal planning app for busy professionals" Output:

Markdown
# Business Idea Analysis: SmartMeals AI

• Concept: AI meal planner optimizing nutrition, time, and budget for working professionals
• Market Size: $12B meal kit/planning market, 8% annual growth
• Feasibility Score: 8/10
• Key Insight: High demand but crowded market requires strong differentiation

Target Market

• Working professionals (25-45), household income $75K+
• 45M potential users in US, growing segment
• Pain points: time constraints, nutrition goals, food waste

Competition

• Direct: PlateJoy, Eat This Much, Mealime
• Indirect: HelloFresh, Blue Apron, grocery apps
• Gap: AI-powered optimization for specific dietary constraints

• Technical: 6/10 - ML models complex but achievable
• Financial: 8/10 - Subscription model proven, $15-25/month viable
• Market: 9/10 - Strong demand signals, growing health consciousness
• Operational: 7/10 - Need nutrition expertise, recipe database licensing

GO - Proceed with MVP focusing on specific niche (e.g., keto, diabetes)

• Next steps: Validate with 100 target users, build recipe partnerships
• Risk mitigation: Start with rule-based system before AI complexity

**Example 2:**
Input: "Drone delivery service for rural areas"
Output: Feasibility score 4/10 due to regulatory hurdles, infrastructure costs, and limited market density making unit economics challenging.

• Start broad, then narrow: Begin with industry overview, drill down to specifics
• Use multiple data sources: Industry reports, competitor websites, customer surveys, expert interviews
• Quantify everything possible: Market size, pricing, costs, timelines
• Consider implementation phases: What's the MVP vs. full vision?
• Address regulatory factors: Compliance requirements, licensing, legal barriers
• Validate demand signals: Search trends, competitor traction, customer interviews
• Be objective: Present balanced view including negative findings

• Confirmation bias: Don't cherry-pick supportive data only
• Over-optimistic projections: Use conservative market penetration assumptions
• Ignoring operational complexity: Factor in hiring, training, scaling challenges
• Underestimating competition: Include indirect competitors and potential new entrants
• Skipping customer validation: Don't rely solely on secondary research
• Missing regulatory requirements: Research compliance costs and barriers early
• Focusing only on features: Emphasize market need and business model viability