Irrespective of your personal political persuasions, for most of us, the 2016 presidential election result was a surprise. Prediction guru Nate Silver was wrong twice-in predicting the winner of the Republican primary and then again with the presidential election. What happened? What caused the massive, well-funded Clinton machine to be up-ended? Various explanations abound from the electoral college (of course), to the geographic concentration of Clinton voters, etc. However, these facts only tell part of the story.
We turn to market research for the answer, and, in a word, that answer is psychometrics.
Psychometrics measures and tracks the values, beliefs, attitudes, interests, and lifestyle of an individual or group. Correspondingly, qualitative data attempts to describe the qualities and characteristics of customers (or, in the case of the election, voters). In essence, qualitative data defines why customers are drawn to an offering.
Today’s Big Data world tends to focus on the crisp precision of quantitative data. Neat spreadsheets and impressive charts or graphs are generally easier to deal with than the murky waters of qualitative data. On the rare occasions qualitative data is made available to researchers, it is presented indirectly in forms such as focus group reports on ad campaigns. With all the transactional data at their disposal, more companies are tempted to ignore the pearls of wisdom to be found in qualitative research. In short, resources are not being dedicated to in-depth qualitative analysis.
By understanding customers’ motivations, you begin to understand how you can better meet their needs and appeal to prospects with similar psychometrics. Qualitative research is particularly important today because buyers have more power and control over the buying process. Figuring out how to appeal to the customer on a personal level through qualitative research becomes a competitive advantage for any company who chooses to embrace it.
Quantitative research allows marketers to draw conclusions based on the correlation of purchase and demographics. This is an important tool and shouldn’t be ignored, however, if quantitative data is allowed to overshadow it’s qualitative counterpart, your company (or party) may lose out.
If you enjoyed this post, subscribe to our blog for future posts in The Qualitative Edge series. For more insights on the value of qualitative research, we recommend “Competing Against Luck”, by Harvard professor Clayton Christensen.
Heather Carpenter is Marketing Manager for Silicon Valley Research Group.
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Topics: Qualitative Research