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:

# 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:

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.