The discovery that more than 99% of the brain processes are non-conscious is forcing a relook at our approach to human behaviour. Among others, one practice that will be most affected by this new discovery will be consumer research, our key conduit to understanding human behaviour.
Traditional consumer research is based on the belief that humans are conscious of their actions and the rationale for those actions. Research techniques like personal interviews and focus group discussions assume that respondents are able to accurately describe their past actions, the reasons for those actions, and are also able to accurately describe what they will do in the future.
For instance, research aimed at understanding the open defecation problem showed that respondents thought that the primary reason for their behaviour was the lack of accessible toilets. Based on this response, millions of toilets were built all over the country. But the open defecation problem remains unsolved. Why? Because there are many more factors that result in open defecation than the absence of toilets. For instance, people felt they needed to spend more time in the toilet, than when defecating in the open. This faulty perception arises because of the way the brain processes the passage of time in a dark environment. For the brain, time stretches in dark spaces.
The respondents, however, only articulate those issues that they are aware of at a conscious level. This inability explains the huge gap that exists between what people say and what they do in many behavioural issues that have policy implications. As the famous neuroscientist Christof Koch puts it, “The perennial habit of introspection has led many intellectuals to devalue the unreflective, non-verbal character of much of life and to elevate language to the role of kingmaker.” Policies and corporate strategies dependent on research techniques that use introspection and verbal reports are on shaky ground.
Another tool that is increasingly being used to understand human behaviour is Big Data and predictive analysis. The ability to record and quantify several facets of human life has given rise to this emerging trend. The assumed accuracy of data and the assurance of very large numbers have made many believe that they have the ultimate tool to plot the intricacies of human behaviour.
The correlations we derive from past behaviour data will give a few indications as to what could trigger the same behaviour subsequently. But mistaking these correlations for causation is a common mistake with big data analysis. According to Viktor Mayer-Schönberger and Kenneth Cukier, authors of the book Big Data: A Revolution That Will Transform How We Live, Work, and Think, “causality won’t be discarded, but it is being knocked off its pedestal as the primary fountain of meaning.”
Past data is quite redundant when the focus is on changing an existing behaviour and replacing it with a new behaviour. For instance, while it could be useful in getting people to switch brands of toothpaste, big data is limited in its ability to provide insights that get people to brush at night. When we use our past understanding of human behaviour to develop future strategies and policies, what one does is less important when compared to the “why”. Understanding the “why” of decisions requires us to decipher the contextual factors, beliefs and emotions that drive those decisions—the non-conscious elements.
Emotions generated during any decision-making process have a significant impact on behaviour. New studies are throwing light on the multiple sub-processes that occur in the brain as an emotion is generated. Many of these occur simultaneously in a matter of milliseconds. On the face of it, emotions like guilt and shame might not seem vastly different, but they are both associated with different action tendencies—with guilt, the action tendency is corrective, whereas the action tendency associated with shame is avoidance and withdrawal. A research technique that is sensitive to these sub-processes is crucial to understanding and explaining behaviour.
Several facets of human behaviour are due to the influence of evolutionary and cultural forces on our brain. For example, one of the main reasons why tens of trespassers die everyday crossing railway tracks is a processing deficiency in the human brain. The insight that the human brain is deficient in judging the closing speed of large objects, like trains, could not have come from focus group discussions with trespassers or analysis of past accident data.
Equally, there are several factors in the environment that affect one’s behaviour. Not just the physical environment, but factors such as social norms—commonly accepted practices in that society—that affect our behaviour without us consciously being aware of them. Traditional research techniques do not really account for the importance of these contextual factors.
Traditional research techniques and big data analysis are moving away from both the context of the consumer, and the consumer himself. Market research is increasingly dependent on third parties, whether it is to conduct research or to obtain data. One should be wary of third-party research and data as they are devoid of these contextual factors. Instead, one needs a research technique that goes closer still to the consumer, to the real context in which the behaviour is occurring. One should be able to really see, touch and smell the problem. Only then could we hope to understand the non-conscious processes behind behaviour.
Biju Dominic is the chief executive officer of Final Mile Consulting, a behaviour architecture firm.
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