The quantitative vs. qualitative research debate has gone on since the 1970s. Apparently it’s all about epistemology, a branch of philosophy concerned with the theory of knowledge. Quantitative research is described as positivism i.e. scientific and objective. Whereas qualitative research is interpretivism i.e. non-scientific and subjective.
The pros and cons of quantitative vs. qualitative research
But there is an academic argument that the two methods cannot and should not work together.
“The chief worry is that the capitulation to “what works” ignores the incompatibility of the competing positivistic and interpretivist epistemological paradigms that purportedly undergird quantitative and qualitative methods, respectively”(1). Blah, blah, blah…
Haven’t quantitative and qualitative research started to overlap already?
The blurring of lines between qualitative and quantitative research has gone on for some time. How many times have you attended research groups and a done a quick ‘tally’ of responses to gain some quantitative guidance? Or, within a quantitative omnibus, included a few open-ended questions to give a little more colour? Superficial instances admittedly, but evidence of ‘blurring’ nonetheless.
Perhaps the reason overlap has not been fully acknowledged is because many believe the disciplines still work separately? Or is it because as you become a ‘quali’ or a ‘quanti’ researcher you are boxed at birth and compartmentalised?! So never the twain shall meet? There is some truth in this as many researchers tend to train under one discipline and most large research organisations run separate quantitative and qualitative departments.
However, from someone “on the ground”, as a qualitative researcher (and perhaps once somewhat fearsome of quantitative research) it is possible to marry these two approaches together and get extra benefits. There is room for a new model, a better hybrid of qualitative and quantitative research. Here are some examples:
Qualitative with added quantitative
Qualitative research discussions often include a few ‘wishy-washy’ answers to questions. Thus it can be difficult to discern differences in meaning. For example, in what one person says they ‘like’ versus another, as well as in overall shades of ’like’, ‘love’ etc. Using simple quantitative measures, such as a rating out of 10, provides much more clarity and decision-making substance.
For example, used within a new product development (NPD) process it can aid selection and refinement and help make sure you are not wasting thousands of hours and pounds barking up the wrong tree!
Rather than asking consumers who ‘likes’ what, by asking them to give a numerical rating on product purchasing intent or to select a number of ‘would definitely try or buy’ product ideas helps focus time and energy on the ideas that matter. This can provide a more useful ‘gate’ in a typical NPD process and enable better short-listing and prioritisation.
Quantitative with added qualitative
Quantitative data sometimes includes open-ended questions to explain the numbers. But in many cases it doesn’t explain anything because respondents have failed to fill in the boxes or the responses are insufficiently detailed. The data of course can also be very costly to collect and cumbersome to analyse.
However, with more creative and combined qualitative-quantitative research it is possible to assess and improve products from food and drink to media and beyond. In a recent project, respondents tasted and then critiqued a number of competitive food products. Research was undertaken in a high traffic place to recruit people off the street into a hall. By gathering consumers’ responses on a questionnaire, and through discussion, it was possible to understand their reasoning as well as brand fit and opportunities for product improvement.
This piece of work was hugely beneficial in providing clear guidance and recommendations for product and brand refinement, as well as proving highly cost-effective. The same techniques also apply to assessments in other categories, such as services and media.
It’s the same with packaging research. For example, at the pack refinement stage to obtain a clear read on stand-out, and the reasoning behind stand-out. By co-opting a minimum of 100 consumers to check a mocked-up retail fixture rotated with current packs and proposed new pack designs and then asking them to complete a short questionnaire. By identifying the appealing packs and critiquing them within the visual noise of a fixture, a numerical assessment of stand-out can be obtained. Adding in a follow-up qualitative discussion to deconstruct and reconstruct the pack elements provides understanding behind the quantitative responses.
There will always be a role for ‘pure’ qualitative and quantitative research approaches but research doesn’t need pigeon-holing into either qualitative or quantitative.
So consider designing qualitative-quantitative research to offer the benefits of both methods. Include face to face contact with consumers to understand as well as gain numerical responses. Within this it is also possible to set quotas for consumer types. All also helps save time and money. Marketers just need to decide what they really need. Do you need understanding or numbers? Or both? A creative research agency should guide and inspire their client or prospective new client, even if it goes against what’s in the brief.
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(1) Against the quantitative – qualitative incompatibility thesis (or dogmas die-hard) by Kenneth R. Howe, Ph.D – Professor of Philosophy at University of Colorado, Boulder Published in the Educational Researcher 17(8) 10-16 1988