Evidence-Based Innovation Blog

MBA Brand Research: Qualitative or Quantitative first?

Posted on Jan 26, 2011 9:02:00 AM

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Higher education market research often involves both qualitative methods (MBA alumni focus groups, incoming student bulletin boards, etc.) as well as quantitative methods (alumni engagement surveys, business school image and awareness surveys, etc.) for complex projects – see comparison.

Once it is determined that qualitative and quantitative research is required to meet the goals of a research study, the next key question is: which one comes first?

Often, this question can be answered by considering where on thelearning curve” one is with the area of study being investigated.

Qualitative before Quantitative:
Exploring early in the learning curve

If a topic or concept is being explored for the first time, or is being considered for a totally new application, then qualitative research is likely the first step in the research design. This approach is often chosen because qualitative methods offer a path to truly understand consumer thought and reaction in the broadest sense, which is often required before the numerical definition and validation offered by quantitative research.

An example of this approach is the initial phases of an curricular or program format redesign study, where focus groups can be employed to uncover the various areas that students feel are important to choosing their MBA program, which could then be later generalized to the school’s prospective student audience in a quantitative image and awareness study. New trends in the MBA market can also be initially defined for further exploration in a qualitative phase.

Moreover, a qualitative phase can provide a forum for stakeholders to help brainstorm or develop an idea into one that could eventually be a compelling one to their peers, which could then be tested in final form in a quantitative study. This type of evidence-based innovation can often be an efficient way to develop a new, distinctive business school marketing strategy, and specific marketing campaigns.  

Finally, when early in the learning curve, academic institutions often do not know “how” to speak to target audiences about specific topics or ideas. Qualitative research can often show researchers how stakeholders speak “naturally” about specific ideas or topics; this learning can then be used to define specific wording within such quantitative research tools as an MBA alumni satisfaction survey or broader student assessments.

Quantitative before Qualitative:
Expanding understanding later in the learning curve

If a topic or concept has been researched effectively in the past, for a given application, then there is often a need to quantitatively benchmark responses with more current data before progressing into a qualitative phase. Tracking studies, such as a MBA lifecycle analysis, provide a strong example where an benchmark assessment survey is required to update understanding before digging in further through a qualitative phase.  

Moreover, if there are syndicated research studies that are readily available which provide some general understanding of things like a certain MBA market arena, then a more customized survey (such as an MBA attitudes and usage survey contexting syndicated data for a specific school or program) is often necessary. This type of survey would likely need to be executed before proceeding further into qualitative research.

Note that, in both of these areas, qualitative research is still a beneficial component to understand the “whys” or “hows” behind the quantitative data. However, in those situations where a research topic is further down the learning curve, it is often best to first understand quantitatively what the key questions or areas of further exploration are, before engaging qualitative research to understand them. 

 

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Dinesh Mathew, the guest writer for this article, is a marketing consumer research expert and qualitative research consultant. Dinesh welcomes your questions and comments.

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Topics: Dinesh Mathew, Qualitative Research, Quantitative Research