brain_icon_color_orange This is the first post in ZS’s Cognitive Drivers Impact Series.

shutterstock_265905926It’s an election year, which means that the news media’s Soren-esque eye is focused on politics and caucuses, most recently in Iowa and New Hampshire. The two states combine for only 10 electoral votes, so why do they receive so much attention?

Winning these first rounds is important because it sets a psychological precedent and bias in voters. People believe that if Candidate X was successful in the recent past, he is more likely to repeat that behavior in the future, which impacts how people vote. People may not realize that they have this bias, but they do. This insight, known as recency bias, is one example of hundreds of cognitive drivers that subconsciously influence how we think and act.

In what ways could clever candidates (and marketers) either take advantage of recency bias if they won, or combat it if they lost?

Applied cognitive science, or the “science of decision making,” is focused on leveraging decades of peer-reviewed academic research to gain insight into why we believe and behave the way we do. In any given instance, a multitude of cognitive biases are operating in parallel, compounding or conflicting with each other to subconsciously influence our beliefs and behaviors.

Understanding how these biases impact decision making can lead to deep, new insights into why consumers and other stakeholders make what seem to be totally irrational or even inconsistent decisions in some circumstances. Armed with this understanding, innovative marketers are able to develop more effective communication strategies and tactics.

This is the first post in ZS’s new Cognitive Driver Impact Series, during which we’ll share different cognitive biases and discuss how they subconsciously influence our beliefs and behaviors. Do you have a cognitive bias or example that you’re interested in learning more about? Please comment on this post to let us know, and stay tuned.


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Topics: Seth Goodman, decision making, recency bias, caucus, presidential candidate, Cognitive Drivers Impact Series