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Research Methodologies
July 1, 2016
Qualitative research has long had perceived drawbacks of scaling. With advances in sampling, outreach platforms, and text analytics, this is changing. The ability to ask and analyze at scale has given rise to a different breed of qualtative research.
By Adam Rossow
The qualitative research renaissance is in full swing. Brands have figured out that context is the key to understanding what’s relevant. And, we have seen through countless examples that left to its own devices, data of any size can lead to missteps based on assumptions.
Despite qualitative’s growing value, drawbacks, both perceived and actual, are still a drag on the more touchy-feely research discipline. A major one being its lack of scale. Many people need the security blanket of large base sizes; the ability to say “3000 people said this”, even if that mass response is too vague or cloudy to prompt action.
It’s understandable. There is always safety in numbers.
But qualitative is branching out. While it’s still the home of the intimate focus group and in-depth individual conversations, it can also be the vehicle that empowers 1,500 consumers to paint a picture of the type of person that stays at an Airbnb, or the platform for 1000 digital natives to provide insight into technology’s role in the shopping experience.
Thanks to advances in sampling, outreach platforms and text analytics, quickly launching a series of open-ended questions to the masses is possible. And, extracting insights from a mountain of responses isn’t nearly as tedious or susceptible to missteps and vagaries as it used to be. That ability to ask and analyze at scale has given rise to a different breed of qualitative. And while a few questions don’t provide the same depth as hour long IDI’s, they do provide a valuable utility for brands – that of quick contextual insight from a large number of individuals.
With just a few open ends clients can get an up to the minute view of their customers, understand if what they are communicating to consumers resonates, uncover which product features are most important, see how their competition is perceived, and more.
Despite needing only a few key ingredients to achieve qualitative at scale, the recipe for success in not so simple. Anyone who has experience working with open ends and text analytics has seen their fair share of one-word answers, word clouds, and uninformative findings. Effectiveness lies in meticulous question formulation and testing, as well as analysis that provides a story, not just word counts and nebulous themes. As with any good qualitative initiative, preparedness and skilled people are vital.
So next time you need answers from the masses, don’t immediately default to quantitative research that’s void of context. You may be missing out on the opportunity to have your scale and your story too.
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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
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