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Marketing research isn't just about collecting data—it's about understanding why consumers behave the way they do and how you can use that knowledge to make smarter business decisions. You're being tested on your ability to distinguish between research methods, match the right method to specific business questions, and understand when qualitative insights trump quantitative data (and vice versa). The underlying principles here—validity, reliability, primary vs. secondary data, and the quantitative-qualitative spectrum—show up repeatedly in exam questions.
Don't fall into the trap of memorizing definitions in isolation. Instead, know what type of insight each method produces, when to deploy it, and what limitations it carries. If an exam question describes a business scenario and asks which research method fits best, you need to think about data type, cost, time constraints, and depth of insight. Master the reasoning behind method selection, and you'll handle any application question thrown your way.
These methods generate numerical data you can analyze statistically. They're designed for breadth over depth—reaching large samples to identify patterns, test hypotheses, and make generalizable claims.
Compare: Surveys vs. Online Analytics—both generate quantitative data, but surveys capture stated preferences while analytics capture revealed behavior. When self-reported data conflicts with actual behavior, analytics often tells the truer story. FRQ tip: If asked about measuring purchase intent vs. actual purchases, this distinction is key.
These methods prioritize depth over breadth. They explore motivations, emotions, and meanings that numbers alone can't capture—generating rich insights from smaller samples.
Compare: Focus Groups vs. Interviews—both are qualitative, but focus groups reveal social influences on opinion while interviews uncover individual depth. Use focus groups when group dynamics matter (e.g., fashion trends); use interviews for sensitive topics where peer presence might inhibit honesty.
These methods bypass self-reporting entirely. By observing consumers in context, researchers capture what people actually do—not what they say they do.
Compare: Observational Research vs. Ethnographic Research—both watch behavior, but standard observation is typically shorter and more focused (e.g., watching shoppers navigate a store aisle), while ethnography involves deep cultural immersion over time. Ethnography answers "What role does this product play in someone's life?" rather than just "How do they use it?"
These methods leverage existing information rather than generating new primary data. They're efficient starting points that inform whether (and how) to invest in primary research.
Compare: Secondary Data Analysis vs. Social Media Monitoring—both use existing data, but secondary analysis draws from formal research and reports while social monitoring captures informal, real-time consumer voice. Secondary data offers rigor and historical depth; social data offers immediacy and authenticity.
| Concept | Best Examples |
|---|---|
| Quantitative/Statistical Analysis | Surveys, Experimental Research, Online Analytics |
| Qualitative/Exploratory Insights | Focus Groups, Interviews, Customer Feedback Analysis |
| Observing Actual Behavior | Observational Research, Ethnographic Research, Online Analytics |
| Establishing Cause-and-Effect | Experimental Research |
| Cost-Effective Starting Points | Secondary Data Analysis, Social Media Monitoring |
| Real-Time Data Collection | Online Analytics, Social Media Monitoring |
| Deep Cultural Understanding | Ethnographic Research |
| Testing Concepts Before Launch | Focus Groups, Experimental Research |
A company wants to understand why customers abandon their shopping carts online. Which two methods would provide complementary insights—one showing where abandonment happens and one exploring why?
Compare and contrast focus groups and ethnographic research. In what scenario would ethnography be worth the additional time and cost investment over a series of focus groups?
A brand suspects that a new packaging design increases purchase likelihood. Which research method would best establish whether the design causes the increase, and why is this method superior to a survey for this question?
You're analyzing customer reviews and notice recurring complaints about a product feature. What type of data is this (primary or secondary, quantitative or qualitative), and what method would you recommend to quantify how widespread the problem is?
An FRQ asks you to design a research plan for a company entering a new international market. Which methods would you sequence first, second, and third—and what does each stage accomplish that the previous one couldn't?