In a business environment that generates millions of data points a day, qualitative market research has become more important than ever. Hard numbers can be generated faster and processed easier than ever before, yet the charts and graphs almost never tell the full story. A hundred million people might give the same response to a question but with a hundred million different reasons for “why.”
Only qualitative data can flesh out the how and why of end-consumer responses. These insights give businesses the ability to look behind the scenes of quantitative data collection and give a story to those trend lines and pie charts. With the latest networking and qualitative research capturing, brands can have the answers and actionable responses they need to make important day-to-day decisions with less fear of the unknown.
Quantitative vs. Qualitative Data — Yang to the Yin
Market research and analysis gives your brand the power to not go into decisions blind. Almost everyone knows this fact, but how they react has become a bit too by-the-numbers, literally. They focus entirely on quantitative data as an ends, not a means. Services like social media, PPC and web hosting yield truckloads of information that can actually mean very little. Without a face and an opinion behind the data, misinterpretation or the false appearance of trends could lead brands astray.
This shortcoming is where qualitative research comes in. Rather than merely “crunching numbers,” text-based, thoughtful responses can give specific reasons that drive consumer behavior. Businesses can use this information to enhance their decision making and bolster their data with insightful narratives. Only this type of deep research can reveal what makes a brand succeed or fail.
Analytical to a Fault
Part of the problem with a quantitative-only approach is that the numbers cannot be significant on their own. Statistical analysis must be used not only to chart trends, but also to form and test hypotheses that inform vital decisions. Researchers (or analytical software) must always find ways to interpret data according to preconceived notions — their hypothesis. This approach can often lead to ignoring important factors that may not fit conveniently within the graph.
Professor of sociology Russell K. Schutt tells us that, by contrast, “qualitative data analysis tends to be inductive — the analyst identifies important categories in the data, as well as patterns and relationships, through a process of discovery. There are often no predefined measures or hypotheses.” An open mind and a tendency for unearthing the surprising gives each test subject a spotlight, where quantitatively they would have been mashed together with other respondents or rejected as an outlier. Schutt emphasises that part of the process of quantitative analysis is to “celebrate anomalies” and outliers because “they are the windows to insight.”
Let’s Make It Personal
With the text-based capture and reseacrh tools created by GroupQuality, finding these transformative nuggets of qualitative information has become easier than ever before. Users can log onto our cloud-based software from any workstation in the world to take part in community discussions, one-on-one interviews and moderated live group.
These activities help your business decipher the impersonal numbers and give them lives, names and background stories. GroupQuality keeps it all together and makes it simple to capture the qualitative information brands need to give sense and true meaning to those mountains of quantitative data.
GroupQuality® is a cloud based customer feedback and insights software and service that helps you capture consumer insights, in less time, on smaller budgets and with fewer resources. If you need a fast and flexible tool to engage customers, employees and partners, to communicate, collaborate, ask questions and quickly capture the answers, then we are for you!
This article first appeared @ groupquality.com/blog