How Do Qualitative and Quantitative Research Differ?

For market researchers, the distinctions between qualitative and quantitative research are very clear, even to the point where many researchers specialize in one or the other of these two types. If the difference is so clear in our minds, then why is it so difficult to write a clear, straightforward, practical and meaningful explanation of the difference?
Most explanations of the qualitative/quantitative distinction tend to focus on listing the typical methods used for each. But this puts the emphasis on the means – the way the data is collected. The more important issue in thinking about the qualitative/quantitative distinction is on the ends. It is the type of research questions you are trying to answer, and more importantly, what type of information would count as a meaningful answer, that determines whether your approach should be qualitative, quantitative or a mix of both.
For example, if your research question is about how some behavior or opinion is distributed across different groups of people, geographic areas or across time, you need numbers – usually percentages – to make these comparisons. This sort of numerical comparison implies a quantitative approach and all the methodological trappings that go with it, including:

• Closed-end survey-type questions
• Relatively large numbers of research participants or direct observations
• A sampling approach that ensures that you have the statistical validity to project the findings from your sample onto the population you are interested in

In contrast, if your research questions are less about comparisons and more about understanding chains of logic, decision processes, group norms, reactions to ideas or sensory stimuli, or cultural domains, you probably need a qualitative approach. Qualitative research focuses on understanding the human experience in context by either:

• Directly embedding the research in the scene or cultural setting (ethnography)
• Using group dynamics to explore norms, attitudes, reactions and beliefs (focus groups)
• Employing inductive questioning to probe reasoning, causation and psychology (in-depth interviews)

In short, it is knowing both the research question and what counts as an answer to the question that determines which “toolkit” the researcher will turn to for a specific project.
That said, the stage of our knowledge about a topic is often an important factor. When we first begin learning about a new topic we are usually in an exploratory mode. We may still be developing our vocabulary about the topic and couldn’t write a good survey about it if we tried – we don’t know enough to write good closed-end questions! Qualitative research is often used at this stage. The very “hands-on” qualitative techniques enable us to learn the lay of the land – how consumers think and speak about the topic. When we see research objectives using verbs like explore or identify – we are usually at this stage of knowledge and lean toward qualitative techniques. We may also use qualitative research at a later stage of knowledge to help interpret quantitative data. In these cases we use interviews or focus groups to understand the correlations that appear in survey data.
Quantitative studies are usually done only in areas where we already have the appropriate knowledge and vocabulary to design good survey questions. We have to know enough about what to ask about, how to ask it, and who to ask it of, to meaningfully quantify the responses. Research objectives that include words such as test, measure or evaluate are more typical of this stage of knowledge.
In short, thinking about qualitative and quantitative research is not about choosing methods or techniques – it is about understanding the nature of your research questions and having a good sense of what type of data – percentages, narratives, images, word counts, observations, maps of logic chains or decision processes would provide useful answers. If you are clear about what you are asking and what you need to know, the choice of methods will largely take care of itself.