Market Analysis Curriculum
Learn to interpret market behavior, assess competitive positions, and build frameworks for strategic decision-making. This program covers practical methods used by analysts working with real commercial data.
What You'll Study
Six modules covering data collection, pattern recognition, competitive assessment, and practical forecasting methods.
Data Foundations
Start with identifying reliable sources and structuring information for analysis. We cover public databases, industry reports, and methods for validating what you find.
- Source evaluation criteria
- Data cleaning techniques
- Building reference libraries
- Tracking changes over time
Market Segmentation
Break down broad markets into meaningful segments. You'll practice identifying customer groups, defining boundaries, and sizing opportunities based on available evidence.
- Demographic vs behavioral splits
- TAM/SAM/SOM calculations
- Geographic considerations
- Segment prioritization logic
Competitive Mapping
Build frameworks to compare competitors across multiple dimensions. Learn to position offerings, identify gaps, and understand how markets perceive different options.
- Feature comparison matrices
- Pricing tier analysis
- Market share estimation
- Positioning maps
Trend Analysis
Recognize patterns in historical data and assess their relevance to future planning. We work with growth rates, seasonal patterns, and disruption indicators.
- Time series interpretation
- Moving averages and smoothing
- Identifying inflection points
- Technology adoption curves
Customer Research
Design surveys, conduct interviews, and extract insights from qualitative feedback. Balance what people say with what they actually do when making purchase decisions.
- Survey design principles
- Interview techniques
- Response bias recognition
- Synthesizing feedback
Forecasting Methods
Build scenarios and projections that acknowledge uncertainty. Learn when to use different forecasting approaches and how to communicate ranges rather than single numbers.
- Bottom-up vs top-down models
- Scenario planning frameworks
- Sensitivity analysis
- Presenting uncertainty
Your Learning Path
Week 1-2: Data sources and structure
Week 3-5: Segmentation and competition
Week 6-7: Customer insights
Week 8: Real project work