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January 23, 2018. Today on RBDR:
OdinText’s Tom Anderson blogs about a change bubbling in the research relationship between qualitative and quantitative. He explains it is mostly about available sample, which is tripping up half of market researchers.
Read Tom Anderson’s blog post by clicking here.
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Hi Bob,
We met at TMRE a year or so ago– just as our beloved Mets were being blown out in the World Series. I still recall your story about riding your bike to watch The Big Shea being built.
Bob, I wanted to add a coda to your qual/ quant broadcast. As a quant shop, we’re big believers in the power of qual leading into quant. You covered that nicely today, and we recommend and conduct that scenario often.
However, there are times when quant/ qual– in reverse order as above– is a compelling tool. The qual portion adds shading to the quant that quant alone cannot always achieve.
Here’s an example: a client wanted to change packaging for a frozen microwaveable food. The change, in addition to a new shape, included moving from a paper to a plastic package. The CLT quant project did its thing, evaluating the viability of the new package to both the current franchise and a relevant audience of competitive users. The former group was recruited to ensure against alienation, the latter to gauge the ability of the new package to capture additional market share.
The qual was conducted among a subset of respondents immediately after the quant. We had an “ah ha” moment with the qual.
Many of the qual participants voiced concern with microwaving a plastic container. This was not an issue with the current paper package. With the plastic container, consumers stated in the qual that they would need to transfer the contents into a microwave safe container prior to heating. The result was that this “convenience” food was now perceived as inconvenient.
Although the quant indicated acceptance of the new plastic package, the accompanying qual raised a red flag that would not have been otherwise detected.
This is an example of how qual immediately after quant can provide insightful information, and this is a tool that researchers ought to consider.
Thanks, Bob. Keep up the good work, and Let’s Go Mets!
This is not about quant before or after qual. This is about more and more qual becoming quant as samples increase and text analytics are used to identify real statistical patterns, and of course getting benefits if Qual by finally taking full advantage of open-ends in quant making the differentiation between ‘qual’ and ‘quant’, meaningless. You can get deeper insights without giving up representation and statistics, you can have your cake and eat it too, better, cheaper, faster