Market Analysis Specialist Course

Lesson 1 • Defining Markets and Market Boundaries

Establishes what constitutes a market and how analysts draw boundaries. Provides the conceptual base for all subsequent segmentation and sizing work.

Lesson 2 • The Market Analysis Process

Maps the end-to-end workflow from problem definition to insight delivery. Connects each phase to deliverables expected in professional practice.

Lesson 3 • Core Analytical Frameworks

Introduces structured models used to assess market attractiveness and competitive dynamics. Equips students with reusable tools applicable across industries.

Lesson 1 • Prioritising and Targeting Segments

Applies scoring matrices to rank segments by attractiveness and strategic fit. Links segmentation output to targeting decisions and resource allocation.

Lesson 2 • Market Sizing Approaches

Teaches top-down and bottom-up sizing methodologies with worked examples. Students understand when each approach is appropriate and how to combine them.

Lesson 3 • Segmentation Methods and Validation

Applies clustering logic and scoring models to form and test segments. Validates segment viability using measurability, accessibility, and profitability tests.

Lesson 4 • TAM, SAM, and SOM Estimation

Defines and quantifies total, serviceable, and obtainable market layers. Students build structured models that support investment and go-to-market decisions.

Lesson 1 • Secondary Data Source Landscape

Maps the ecosystem of commercial databases, government statistics, trade associations, and academic sources. Students identify the most credible sources for each market question.

Lesson 2 • Desk Research Techniques

Teaches systematic search strategies, Boolean operators, and citation tracking for efficient data retrieval. Students build structured research logs.

Lesson 3 • Synthesising Secondary Data

Combines findings from multiple sources into coherent market narratives and data tables. Resolves conflicting data points using reconciliation techniques.

Lesson 1 • Research Design Principles

Covers exploratory, descriptive, and causal research designs and their appropriate use cases. Aligns design choice with the analytical question established in Chapter 1.

Lesson 2 • Qualitative Research Methods

Covers in-depth interviews, focus groups, and ethnographic observation for rich market insight. Students design discussion guides and manage qualitative data.

Lesson 3 • Data Collection and Field Management

Addresses online, telephone, and in-person data collection channels and quality controls. Students manage fieldwork timelines and response rate optimisation.

Lesson 4 • Survey Design and Questionnaire Construction

Builds effective questionnaires using validated question types and logical flow. Students avoid common design errors that reduce response quality.

Lesson 1 • Competitive Benchmarking

Applies quantitative and qualitative benchmarking to compare performance across key dimensions. Produces scorecards that highlight relative strengths and weaknesses.

Lesson 2 • Competitive Landscape Mapping

Creates perceptual maps and strategic group analyses to visualise competitive positioning. Students identify white-space opportunities from landscape gaps.

Lesson 3 • Competitive Intelligence Fundamentals

Defines competitive intelligence scope, ethics, and the intelligence cycle. Distinguishes legal open-source intelligence from prohibited methods.

Lesson 4 • Competitor Identification and Profiling

Identifies direct, indirect, and potential competitors using market maps and substitution analysis. Students build standardised competitor profile templates.

Lesson 1 • Psychological Drivers of Purchase Decisions

Examines motivation, perception, attitude formation, and cognitive biases that influence buying behaviour. Connects psychological theory to observable market patterns.

Lesson 2 • Price Sensitivity and Demand Elasticity

Quantifies how demand responds to price changes using elasticity concepts and conjoint-based methods. Links elasticity findings to pricing strategy recommendations.

Lesson 3 • B2B Buying Behaviour and Organisational Dynamics

Contrasts organisational buying processes with consumer behaviour, covering buying centres and procurement cycles. Adapts demand analysis to B2B market contexts.

Lesson 4 • Social and Cultural Influences

Analyses how reference groups, culture, and social class shape consumption patterns. Students identify cultural variables relevant to target segments.

Lesson 1 • Market Forecasting Methods

Compares quantitative forecasting models including regression, exponential smoothing, and scenario-based approaches. Students select and justify the appropriate method.

Lesson 2 • Descriptive Statistics for Market Data

Uses measures of central tendency, dispersion, and distribution shape to summarise market datasets. Provides the statistical foundation for inferential analysis.

Lesson 3 • Correlation and Regression Analysis

Identifies relationships between market variables using correlation coefficients and regression models. Students interpret outputs and test model assumptions.

Lesson 4 • Time-Series Analysis and Trend Modelling

Decomposes time-series data into trend, seasonal, and cyclical components. Students apply smoothing and decomposition methods to historical market data.

Lesson 1 • Data Visualisation for Market Analysts

Selects and designs charts, maps, and infographics that communicate market data clearly. Applies visual hierarchy and annotation to guide reader interpretation.

Lesson 2 • Presenting Insights to Stakeholders

Adapts insight delivery to executive, technical, and cross-functional audiences. Students structure persuasive presentations that drive decisions.

Lesson 3 • Dashboard Design and KPI Tracking

Builds market monitoring dashboards that track leading and lagging indicators over time. Students define KPIs aligned with strategic market objectives.

Lesson 4 • Structuring Market Analysis Reports

Designs report architecture using pyramid principle and executive summary best practices. Students produce reports that guide decision-making at senior levels.