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Neuroforecasting: Revolutionizing Predictive Analytics

Consumer neuroscience and neuromarketing, rapidly expanding fields, provide unparalleled insight into the decision-making process of consumers that goes beyond traditional self-report methods, offering new avenues for marketers to improve their campaigns. In our previous blog post, we highlight neuromarketing methods and capabilities and how it supplements traditional techniques such as focus groups, surveys, etc... Here, however, we will discuss what every marketer wants to know, what is the best way to predict real-world outcomes from a marketing campaign?


The conventional methods that rely on self-report typically only predict an individual’s behavior and not the future behavior of the population. Additionally, to obtain quality data from self-reported methods, researchers hope that participants accurately reflect on their mental processes. For example, asking participants what they will do in the future (e.g., how likely are you to purchase this product?) will yield inaccurate results because people are generally bad at assessing future mental states. In a chapter from the APA Handbook of Consumer Psychology, authors Alexander Genevsky and Carolyn Yoon stated:

“In some cases, the very act of asking individuals to reflect on their internal processes fundamentally changes their experiences in a way that makes them incompatible with the real-world phenomena being examined. Use of neural data to capture what is hidden in consumers’ brains to make predictions may thus provide a window into decision making processes that are informative in improving predictions.”

Prior research demonstrated that using neuroscience yields better purchasing decision predictors than self-reporting. For example, when participants were shown products before they made any purchasing decisions, preferred products increased activity in the nucleus accumbens (an area in the brain for reward processing), whereas excessive price increased activity in the insula (awareness processing) and deactivated the medial prefrontal cortex (valuation processing). These patterns of brain activity significantly predicted future purchasing behavior more effectively than retrospective self-reporting preferences. This research was a step in the right direction to predicting the participant’s future behavior. However, the question remains, can neuroscience methods better predict population-level behavior?


In the previously mentioned chapter, Genevsky and Yoon address this question. They outlined the current state of a growing field called neuroforecasting. In total, the authors reviewed 16 articles (8 EEG, 7 fMRI, and 1 EEG+fMRI) that studied a range of stimulus types (i.e., songs, video ads, movie trailers, products, news articles, crowdfunding appeals, microlending requests, TV programs, and YouTube videos). These articles concluded that neuroscience methods strongly predict population-level outcomes (album sales, online reviews, box office sales, product sales, news article online sharing, funding success, loan funding rates, Twitter activity about TV programs, and online views).


Neuroscience may be the best method to determine population-level outcomes in market research, but one of these articles used an innovative methodology not only to gauge the participants’ interest and recall but also to predict the population’s interest. The research authored by Samuel B. Barnett and Moran Cerf used ThinkAlike Laboratories’ patented methodology, Cross-Brain-Correlation (CBC), to measure neural engagement toward movie trailers in moviegoers. This study, and the CBC method, have already been discussed in our blogs entitled Does Neuromarketing Read Minds? and Cross-Brain-Correlation Measures Unbiased Engagement. However, this research found that not only did CBC predict the participants’ ability to recall the trailers (individual-level behavior), but it also was a strong predictor of opening weekend ticket sales (population-level behavior). Furthermore, the researchers conducted this study in movie theaters, adding real-world validity.


The fast-growing fields of consumer neuroscience and neuromarketing highlight the value of measuring neurological and physiological responses. To show the rate of growth, I used app.dimensions.ai to estimate the number of publications and citations for each year with “consumer neuroscience” and “neuromarketing” keywords, the figure below shows how research has increased over time by looking at the number of publications each year (left y-axis in thousands). Additionally, the increase in citations (right y-axis, in millions) indicates that these publications significantly impact science in marketing and the understanding of information processing, decision-making, and human behavior.

While traditional self-reporting methods are still commonly used in marketing research, neuromarketing provides a more accurate and reliable way of predicting consumer behavior. By examining neural data, researchers gain insight into decision-making processes that may not be accessible through self-reporting. Recent studies demonstrate that neuroscience methods strongly predict population-level outcomes across various stimuli, including products, movie trailers, video ads, and crowdfunding appeals. As the field of neuromarketing continues to develop, it has the potential to revolutionize the way marketers understand and predict consumer behavior and maximize return on investment.

 

Author: Robert Torrence, Ph.D.

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