Customer Analytics and Market Research
Customer research, surveys, analytics, experiments, and evidence-based marketing decisions.
About this course
Customer Analytics and Market Research (MKT 202) teaches you how to turn customer questions into evidence-based marketing decisions. You will move from research strategy to qualitative methods, survey design, customer analytics, experiments, and decision support tools that managers use to allocate marketing spend with confidence.
This is research and analytics for practitioners, not academic methodology for its own sake. The goal is fluency: when someone cites sample bias, statistical power, or cohort retention, you know what was measured, what was assumed, and what the data can and cannot prove.
Prerequisites: MKT 201 (Marketing Management). Length: 3 weeks. Assessment: 40% applied project, 35% knowledge checks, 25% reflections.
What you will be able to do
By the end of MKT 202, you should be able to:
- Translate business decisions into well-scoped research questions and study designs
- Conduct and synthesize qualitative customer research with appropriate ethics and privacy
- Design surveys with valid sampling, reliable measurement, and bias awareness
- Analyze customer data with cohort, funnel, retention, and lifetime value models
- Design and interpret A/B tests and experiments with attention to causal inference
- Build decision-support outputs including dashboards, conjoint analysis, and research briefs
How the course is organized
Six units, 30 lessons. Work in order; each lesson includes worked examples and practice problems.
| Unit | Topic | Lessons | You will |
|---|---|---|---|
| 1 | Research Strategy | 5 | Frame decisions, choose methods, and design research plans |
| 2 | Qualitative Customer Research | 5 | Run interviews, observation, and synthesis into personas |
| 3 | Survey Research | 5 | Design questionnaires, sample populations, and analyze results |
| 4 | Market and Customer Analytics | 5 | Apply cohort, funnel, retention, and CLV analytics |
| 5 | Experiments and Causal Evidence | 5 | Design A/B tests, estimate power, and interpret causal results |
| 6 | Decision Support | 5 | Build dashboards, conjoint models, and research recommendations |
How to study
- Read lessons sequentially. Research strategy frames everything that follows. Skipping survey validity makes experiment design and analytics interpretation unreliable.
- Do the practice problems without peeking. Questionnaire design, sample-size logic, and cohort calculations need hands-on practice.
- Pick one anchor decision. Carry a single marketing question from research plan through data collection to a final recommendation memo.
- Complete unit assessments after all five lessons in that unit. Knowledge checks test application, not vocabulary lists.
Applied work
Across MKT 202 you will build portfolio pieces that compound:
- Applied project: End-to-end research plan with survey or experiment design and analysis
- Case analysis: Two-page customer insights brief with evidence quality assessment
- Portfolio artifact: Customer analytics dashboard with cohort and funnel metrics
- Executive memo: Research-backed marketing recommendations with limitations stated clearly
What comes next
MKT 201 gave you the strategic marketing foundation; this course adds the evidence layer. OMBA 102: Data, Statistics and Managerial Decisions deepens statistical inference and decision analysis that support rigorous experiment interpretation. CAP 600: Program Capstone Studio integrates customer evidence into your final integrated business recommendation.
Assessment
40% applied project, 35% knowledge checks, 25% reflections
Each unit includes a case component aligned to this weight.
Each unit includes a exercise component aligned to this weight.
Each unit includes a reflection component aligned to this weight.
Open any unit below to complete exercises, project tasks, and the knowledge quiz. Units auto-complete when all assessment items are submitted and you score 80%+ on the quiz.