"Research reveals optimal brainwave patterns for optimizing advertising testing"
Brainwave measurement, commonly regarded as the gold standard of ad testing, exhibits variability in its results obtained through electroencephalography (EEG). A recent study published in the Journal of Advertising reveals that one specific EEG metric — intersubject correlation (ISC) — outperforms others in predicting viewer responses to advertisements.
In the study, 116 participants with sensors attached to their heads watched 13 TV commercials. ISC, which measures the similarity of neural responses among viewers, proved to be the most consistent and reliable indicator across all six tested metrics throughout the experiment.Notably, ISC was found to reflect engagement and could reliably differentiate responses to various ad versions and identify reactions to specific commercial segments.
Typically, EEGs measure brain electric signals by placing sensors on the scalp and recording changes in the frequency and amplitude of those signals. After ISC, the metrics most closely associated with attention, arousal, rewards, liking, memory, disliking, understanding, and pleasantness ranked as follows: alpha frequency band, beta frequency band, theta, gamma, and alpha-asymmetry (from high to low reliability).
Motivated by the lack of studies examining EEG metric quality, researchers aimed to evaluate their reliability, particularly in relation to sample size and repeated viewings. Only ISC was rated among the top tier for reliability. Enhancements in reliability could be achieved through increasing sample size or encouraging viewer repetition. While keeping viewers engaged is crucial, viewing the ads three times was determined as the optimal number, as any further viewings may provoke disengagement or boredom.
The study underscores the importance of reliable EEG measures in optimizing commercials to maximize impact. ISC and metrics related to emotional response and cognitive load emerge as promising areas for further research. Utilizing advanced analysis techniques, cross-validation with behavioral data, and integrating EEG data with other physiological signals may help elevate the reliability of EEG in predicting advertising responses.
- The study conducted in the Journal of Advertising revealed that intersubject correlation (ISC) in EEG, a measure of media’s neural responses similarity among viewers, outperforms other metrics in predicting responses to advertising.
- Interestingly, despite the tests on six different metrics, ISC was found to be the most consistent and reliable indicator throughout the health-and-wellness themed experiment, reflecting engagement and differentiating reactions to various ad versions and segments.
- The researchers discovered that ISC, along with other metrics related to emotional response and cognitive load, demonstrated top-tier reliability—improvements may be achieved by increasing the sample size or encouraging viewer repetition up to three times.
- By focusing on reliable EEG measures in ad testing, such as ISC, it becomes possible to optimize commercials, ensuring they will have the maximum impact, and paving the way for further research into the integration of EEG data with other physiological signals like technology and nutrition to refine advertising strategies in fitness-and-exercise, mental-health, and other realms.
