Consumers often share product-related content (e.g., advertising), and highly shared advertising has a huge impact on consumer behavior. Despite its apparent effectiveness, prediction of whether such advertising will be highly shared is a poorly understood area of marketing. Advances in brain imaging techniques may allow researchers to forecast aggregate consumer behavior beyond subjective reports. Using neuroimaging techniques, previous research has established models showing that expectations of self-related outcomes (potential for self-enhancement) and the social impact of sharing (potential for social approval) contribute to the likelihood of users sharing non-commercial static content (i.e., text-based health news). However, whether this finding can be applied to forecasting the virality of dynamic commercial stimuli, which is more relevant to interactive marketing (i.e., video ads), remains unknown. Combining brain imaging techniques, cross-validation methods, and real-world data regarding sharing on social media, the present study investigated whether brain data can be used to forecast the viral marketing success of video ads. We used neuroimaging (functional magnetic resonance imaging: fMRI) to measure neural activity during three sets of theory-driven neural measures implicated in value, self, and social (mentalizing) processes while 40 participants viewed video ads that brands had posted on Facebook. Contrary to previous findings regarding value-related virality in non-commercial static content, our results indicate that social-related neural activity contributes significantly to forecasting the virality of dynamic marketing-related content. The model that included both social-related neural measures and subjective intentions to share forecasted viral marketing success better than the model that included only social-related neural measures. The model that included only subjective intention to share did not forecast viral marketing success. Overall, these findings provide a novel connection between neurophysiological measures and real-world dynamic commercial content. Contrary to previous neuroforecasting findings, social-related but not value-related neural measures can significantly improve our ability to predict market-level sharing of video ads.

消费者经常共享与产品相关的内容（例如，广告），而高度共享的广告对消费者行为产生巨大影响。尽管具有明显的效果，但对此类广告是否将被高度共享的预测仍是市场营销领域一个鲜为人知的领域。脑成像技术的进步可以使研究人员预测除主观报告之外的总体消费者行为。以前的研究使用神经影像技术建立了模型，显示出对自我相关结果的期望（自我增强的潜力）和共享的社会影响（社会认可的潜力）有助于用户共享非商业静态内容（即，基于文本的健康新闻）。但是，这一发现是否可用于预测动态商业刺激的病毒性，与互动营销（即视频广告）更相关的内容仍然未知。这项研究结合了大脑成像技术，交叉验证方法和有关在社交媒体上共享的现实世界数据，研究了大脑数据是否可以用于预测视频广告的病毒式营销成功。我们使用神经影像学（功能磁共振成像：fMRI）在涉及价值，自我和社会（心理化）过程的三组理论驱动的神经测量中测量神经活动，同时40名参与者观看了品牌在Facebook上发布的视频广告。与先前关于非商业静态内容中与价值相关的病毒性的发现相反，我们的结果表明，与社会相关的神经活动对预测动态营销相关内容的病毒性具有显着贡献。与仅包含社交相关神经测度的模型相比，包含社交相关神经测度和主观共享意愿的模型更好地预测了病毒式营销的成功。仅包含主观共享意愿的模型并未预测病毒式营销的成功。总体而言，这些发现提供了神经生理学测量与现实世界中动态商业内容之间的新颖联系。与以前的神经预测结果相反，与社会相关但与价值无关的神经测量可以显着提高我们预测视频广告市场份额的能力。仅包含主观共享意愿的模型并未预测病毒式营销的成功。总体而言，这些发现提供了神经生理学测量与现实世界中动态商业内容之间的新颖联系。与以前的神经预测结果相反，与社会相关但与价值无关的神经测量可以显着提高我们预测视频广告市场份额的能力。仅包含主观共享意愿的模型并未预测病毒式营销的成功。总体而言，这些发现提供了神经生理学测量与现实世界中动态商业内容之间的新颖联系。与以前的神经预测结果相反，与社会相关但与价值无关的神经测量可以显着提高我们预测视频广告市场份额的能力。