Biometrics predict election results better than inefficient polls
Biometrics could predict the results of the upcoming British election better than inefficient polls, says Giuliano Noci, Professor of Strategy and Marketing at Politecnico di Milano School of Management, Italy.
Recent exit poll and market research failures have provided unreliable political predictions, such as during Brexit, the American election and the Italian referendum.
Noci says: “Researchers should not have relied on voters to accurately report their own preferences in recent political votes. Aside from undecided voters, there are also those who lie to disassociate themselves from a vote they believe will make them seem controversial or unpopular. Often, people give the answer they think the interviewer seeks, even if their opinion is completely different. This explains why polls during events like Britain’s referendum and the American election did not accurately reflect the way many ultimately voted.”
Using biometrics to interpret signals such as blood pressure, heart rate and microfacial expressions to measure participants’ emotional reactions to political ideas and stimulus could indicate which way they would really vote.
These biometric tests require only small sample groups and are not invasive, completed on wearable devices.
Noci says: “Biometrics provide a tried and tested means of predicting which way people will vote, and of understanding the drivers behind why people gravitate towards, or away from, individual political ideas and parties. These tests can undermine our defences, such as shame and reserve, to reveal the true secrets of the mind. Not only could using these methods provide a clearer indication of the result of upcoming political votes such as the British election, but political parties themselves could use the findings to better design manifestos that serve the masses, by focusing in on individual reactions.”
For more information, or to speak with Professor Noci, please contact Natalie Bishop of BlueSky PR on (+44) 1582 790 700 or at firstname.lastname@example.org
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