Market Research and Analysis for Tech Industries Course

Lesson 1 • Ethics and Compliance in Research

Covers informed consent, data privacy obligations, and ethical data use. Ensures research practices meet professional and regulatory standards.

Lesson 2 • Types of Market Research

Differentiates primary, secondary, qualitative, and quantitative research. Students select the appropriate type based on business questions.

Lesson 3 • The Tech Market Research Process

Outlines the end-to-end research workflow from planning to reporting. Students map each phase to deliverables and timelines.

Lesson 4 • Defining Research Objectives

Teaches how to translate business problems into precise research questions. Clear objectives prevent scope creep and wasted resources.

Lesson 1 • Mapping the Competitive Ecosystem

Guides students in building ecosystem maps that include partners, platforms, and adjacent players. Ecosystem thinking reveals indirect competitive threats and alliance opportunities.

Lesson 2 • Technology Adoption and Lifecycle Models

Covers diffusion of innovation and product lifecycle models for tech products. Students apply lifecycle stage to research design and market opportunity assessment.

Lesson 3 • Industry Structure Analysis

Applies structural analysis tools to assess competitive intensity in tech markets. Students identify structural forces shaping profitability and growth potential.

Lesson 4 • Defining and Segmenting Tech Markets

Introduces market definition frameworks and segmentation variables specific to tech. Accurate segmentation underpins all subsequent competitive and customer analysis.

Lesson 1 • Digital and Web-Based Intelligence

Covers web scraping principles, social listening, and digital footprint analysis. Students gather and structure digital signals into actionable market insights.

Lesson 2 • Public and Government Data Sources

Identifies publicly available datasets relevant to tech market research. Students access and interpret statistical databases, patent records, and trade data.

Lesson 3 • Evaluating and Synthesizing Secondary Sources

Teaches source triangulation, bias detection, and synthesis frameworks. Students produce a structured secondary research brief with confidence ratings.

Lesson 4 • Secondary Research Fundamentals

Defines secondary research and its advantages and limitations in tech contexts. Establishes criteria for source selection before students access any data.

Lesson 1 • Field Research and Expert Interviews

Guides students in conducting expert interviews and field visits with tech stakeholders. Expert input validates secondary findings and surfaces emerging market signals.

Lesson 2 • Qualitative Research Techniques

Introduces in-depth interviews, focus groups, and ethnographic observation for tech research. Qualitative methods uncover motivations that surveys cannot capture.

Lesson 3 • Sampling Strategy and Recruitment

Explains probability and non-probability sampling methods for tech market populations. Students calculate sample sizes and design recruitment screeners.

Lesson 4 • Survey Design for Tech Audiences

Covers question types, scale selection, and survey flow for technical respondents. Well-designed surveys reduce non-response bias and improve data quality.

Lesson 1 • Inferential Statistics and Hypothesis Testing

Introduces confidence intervals, t-tests, and chi-square tests for market research conclusions. Students determine statistical significance before drawing actionable inferences.

Lesson 2 • Segmentation and Clustering Techniques

Uses cluster analysis and factor analysis to identify distinct customer and market segments. Quantitative segmentation replaces intuition with data-driven groupings.

Lesson 3 • Descriptive Statistics for Market Data

Covers measures of central tendency, dispersion, and distribution shape for market datasets. Descriptive statistics form the baseline for all deeper quantitative analysis.

Lesson 4 • Regression and Correlation Analysis

Applies linear and multiple regression to identify drivers of market outcomes. Students model relationships between variables such as price, adoption, and satisfaction.

Lesson 1 • SWOT and Competitive Positioning Frameworks

Applies SWOT, perceptual mapping, and positioning matrices to competitive data. Students translate analysis into clear positioning recommendations.

Lesson 2 • Monitoring Competitor Signals

Teaches ongoing monitoring of competitor moves through digital and public channels. Continuous monitoring converts reactive intelligence into proactive strategy.

Lesson 3 • Competitor Profiling and Benchmarking

Guides systematic profiling of direct and indirect competitors across key dimensions. Benchmarking reveals performance gaps and informs strategic positioning decisions.

Lesson 4 • Competitive Intelligence Fundamentals

Defines competitive intelligence, its scope, and its distinction from corporate espionage. Establishes an ethical and legal framework before any intelligence gathering begins.

Lesson 1 • Voice of the Customer Programmes

Designs systematic VoC programmes using NPS, CSAT, and qualitative feedback loops. Continuous VoC data tracks satisfaction trends and surfaces emerging needs.

Lesson 2 • Willingness to Pay and Pricing Research

Applies conjoint analysis, Van Westendorp, and Gabor-Granger methods to pricing decisions. Students determine optimal price points and feature-value trade-offs.

Lesson 3 • Customer Segmentation and Persona Development

Combines quantitative segmentation with qualitative insight to build actionable personas. Personas anchor product, marketing, and sales decisions to real customer profiles.

Lesson 4 • Churn, Retention, and Loyalty Research

Investigates drivers of churn and loyalty through cohort analysis and exit interviews. Retention research directly links market insights to revenue protection strategies.

Lesson 1 • Synthesising Research into Insights

Teaches affinity mapping, insight laddering, and so-what analysis to move from data to insight. Synthesis transforms raw findings into decision-relevant intelligence.

Lesson 2 • Presenting to Tech Stakeholders

Develops skills for presenting research findings to technical, executive, and cross-functional audiences. Tailored presentations increase research adoption and organisational impact.

Lesson 3 • Structuring Research Reports

Covers report architecture, executive summary writing, and appendix organisation for tech audiences. A well-structured report increases the likelihood that findings drive decisions.

Lesson 4 • Translating Insights into Strategic Recommendations

Guides students in converting research conclusions into prioritised, actionable recommendations. Strategic recommendations close the loop between research investment and business outcomes.