Don’t look blank, happy, or sad: patterns of facial expressions of speakers in banks’ YouTube videos predict video’s popularity over time

There has been little focus on nonverbal communication in social media advertising campaigns. We propose that specific patterns of facial expressions predict the popularity of YouTube videos among users of social media. To test that proposition, we used a neuromarketing tool—FaceReader—to code facial videos of professional speakers who participated in the YouTube social media campaigns of 2 large commercial banks. We analyzed more than 25,000 video frames of 16 speakers’ 6 basic facial expressions. We found that less incidence of affiliative facial emotions (happiness and sadness) and more incidence of nonemotional expressions (surprise) explained an additional 25% of variance (from 61% to 86%) in the video’s popularity (number of YouTube views) after 8 months in t2 (July 14, 2015), in comparison to t1 (October 31, 2014) as the only baseline predictor. We further showed that the disaffiliative facial emotions of the speakers (anger, fear, and disgust) did not contribute as an indicator of the future performance of social media content. We hope that these findings will open new lines of research in corporate communication by incorporating neuromarketing and nonverbal communication to understand not only what content is effective but how it should be presented.