Editor's note: Chuck Bean is a partner at The Martec Group, a Chicago-based research firm.
Scientists have long known that there is often great disparity between our internal and external selves – how people say they feel about something and their actual, genuine feeling. It’s not that we’re deceptive – it’s often a subconscious process. You might say it’s just human nature. This disparity has been measurable using complex fMRI brain imaging, biometric evaluations, facial scanning technology and other physiological and psychological research techniques. Naturally marketers quickly realized the potential in these technologies: Rather than relying on educated guesses and interpretation, branding and marketing initiatives could be tested with amazing accuracy. Thus, the birth of emotion research.
Lab-based techniques have two major limitations: They are complicated to use and they are not easily scalable to large customer groups. It turns out another way of getting the same insights, without the need for such complex equipment, exists in the form of language-based emotion research techniques. These methods rely on comprehensive word-association dictionaries along with powerhouse computing to dig into what subjects declare via written or verbal response to decipher their true, authentic sentiments, going beyond their surface-level responses.
Here’s an example: An emotion language analysis study was conducted on behalf of a hand-soap manufacturer to find out how consumers feel about handwashing. At first, respondents in this study described their feelings using words associated with pleasant emotions such as security and confidence. But then it got more interesting: As the consumers elaborated further, some surprising differences emerged between women’s and men’s feelings. To most women, the idea of handwashing triggered consistently pleasant emotions. But when men were asked to elaborate, most of their...