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Can Emotions Improve Predictions?

Recently I had lunch with my colleague Michel Pham at Columbia Business School. Michel is a leading authority on the role of affect (emotions, feeling and moods) in decision making. He was telling me about a very interesting phenomenon called the Emotional Oracle Effect – where he and his colleagues had examined whether emotions can help make better predictions. I was intrigued. We tend to think of prediction as a very rational process – collect all relevant information, use some logical model for combining the information, then make the prediction. But Michel and his colleagues were drawing on a different stream of research that showed the importance of feelings. So the question was, can people make better predictions if they trust their feelings more?

To answer this question they ran a series of experiments. As we researchers know, experiments are the best way to establish a causal linkage between two phenomena. To ensure that their findings were solid, they ran eight separate studies in a wide variety of domains. This included predicting a Presidential nomination, movie box-office success, winner of American Idol, the stock market, college football and even the weather. While in most cases they employed a standard approach to manipulate people’s feelings of trust in themselves, in a couple of cases they looked at differences between people who trusted their feelings more (and less).

Across these various scenarios the results were unambiguous. When people trusted their feelings more, they made more accurate predictions. For example, box office showing of three movies (48% Vs 24%), American Idol winner (41% Vs 24%), NCAA BCS Championship (57% Vs 47%) and Democratic nomination (72% Vs 64%), weather (47% Vs 28%) were some of the cases where people who trusted their feelings predicted better than those who did not. This, of course, raises the question of why? What is it about feelings and emotion that allows a person to predict better?

The most plausible explanation they propose (tested in a couple of studies) is what they call the privileged-window hypothesis. This grows off the theoretical argument that “rather than being subjective and incomplete sources of information, feelings instead summarize large amounts of information that we acquire, consciously and unconsciously about the world around us.” In other words, we absorb a huge quantity of information but don’t really know what we know. Thinking rationally about what we know and summarizing it seems less accurate than using our feelings to express that tacit knowledge. So, when someone says that they did something because “it just felt right”, it may not be so much a subjective decision as an encapsulation of acquired knowledge. The affective/emotional system may be better at channeling the information and making the right decision than the cognitive/thinking system.

So, how does this relate to market research? When trying to understand consumer behavior through surveys, we usually try to get respondents to use their cognitive/thinking system. We explicitly ask them to think about questions, consider options and so on, before providing an apparently logical answer. This research would indicate that there is a different way to go. If we can find a way to get consumers to tap into their affective/emotional system we might better understand how they arrived at decisions.

Of course, this will not be easy as both researchers and respondents are conditioned to use the cognitive/thinking system. But if we can move our focus from the instrument (i.e., questionnaire) to the respondent’s mental/emotional state, we may be able to devise ways to get them to respond appropriately.

This may also have another benefit. As researchers, we know there is a gap between answering questions in a survey and making choices in the market place. We often attribute this to respondent (lack of) engagement. Perhaps it is also because real decisions are more influenced by emotions, while survey answers are not. By incorporating respondent emotions into their responses we may get a clearer picture of consumer decision-making.                   

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