--- name: market-analysis-guide description: "Structured frameworks for market sizing, competitive analysis, and strategic ..." metadata: openclaw: emoji: "📈" category: "domains" subcategory: "business" keywords: ["market analysis", "strategic management", "operations management", "competitive analysis", "market sizing"] source: "wentor" --- # Market Analysis Guide A comprehensive skill for conducting rigorous market analysis in academic and applied research contexts. This guide covers quantitative market sizing, competitive landscape mapping, and strategic positioning frameworks grounded in peer-reviewed methodologies. ## Market Sizing Methodologies Market sizing is the foundation of any credible market analysis. There are two primary approaches, and robust research typically employs both for triangulation. **Top-Down Approach (TAM/SAM/SOM)** Start with the total addressable market and narrow systematically: ``` TAM (Total Addressable Market) -> SAM (Serviceable Available Market) -> SOM (Serviceable Obtainable Market) Example calculation: TAM = Global higher-education EdTech spend = $340B (2025, HolonIQ) SAM = AI-powered research tools segment = $12B SOM = Realistic capture in Year 3 = $120M (1% of SAM) ``` **Bottom-Up Approach** Build estimates from unit economics: ```python # Bottom-up market sizing users_in_target_segment = 8_000_000 # global PhD + postdoc researchers adoption_rate = 0.05 # 5% in first 3 years avg_revenue_per_user = 180 # USD/year bottom_up_estimate = users_in_target_segment * adoption_rate * avg_revenue_per_user # Result: $72,000,000 ``` Always cite the data sources for each assumption. Use government statistics (e.g., NSF, Eurostat), industry reports (Gartner, McKinsey), and published academic datasets. ## Competitive Analysis Frameworks ### Porter's Five Forces Apply Porter's framework systematically to map industry structure: | Force | Key Questions | Data Sources | |-------|--------------|--------------| | Rivalry | How many direct competitors? Market concentration (HHI)? | Crunchbase, SEC filings | | New Entrants | Capital requirements? Regulatory barriers? | Patent databases, regulatory filings | | Substitutes | What alternatives exist? Switching costs? | User surveys, app store data | | Buyer Power | Customer concentration? Price sensitivity? | Industry reports, interviews | | Supplier Power | Input scarcity? Vendor lock-in? | Supply chain databases | ### SWOT and TOWS Matrix Go beyond basic SWOT by constructing a TOWS matrix that generates actionable strategies: ``` Strengths (S) Weaknesses (W) Opportunities SO strategies WO strategies (O) (use S to exploit O) (overcome W via O) Threats ST strategies WT strategies (T) (use S to counter T) (minimize W, avoid T) ``` ## Data Collection and Validation Primary data collection methods for market analysis research: 1. **Structured interviews** with industry experts (N >= 12 for saturation) 2. **Survey instruments** validated with Cronbach's alpha >= 0.70 3. **Conjoint analysis** for preference and willingness-to-pay estimation 4. **Web scraping** of pricing pages, job postings, and product changelogs Secondary data sources to cross-validate: - Statista, IBISWorld, Grand View Research for market reports - USPTO/EPO patent filings for technology trajectory analysis - PitchBook/Crunchbase for funding and M&A activity ## Reporting and Visualization Present findings using clear, reproducible visualizations: ```python import matplotlib.pyplot as plt import numpy as np segments = ['Segment A', 'Segment B', 'Segment C', 'Segment D'] sizes = [45, 28, 18, 9] colors = ['#3B82F6', '#EF4444', '#10B981', '#F59E0B'] fig, ax = plt.subplots(figsize=(8, 6)) ax.barh(segments, sizes, color=colors) ax.set_xlabel('Market Share (%)') ax.set_title('Competitive Landscape by Segment') plt.tight_layout() plt.savefig('market_share.png', dpi=300) ``` Always include confidence intervals or sensitivity ranges for quantitative estimates. A well-structured market analysis report should contain an executive summary, methodology section, findings with visualizations, and a limitations discussion.