Effects of multiple models and group diversity in social media advertising

This study examines digital video advertising, focusing on the impact of single versus multiple models on social media responses and the role of group diversity (age, gender, ethnicity) in international ads. Using theories of information utility, message repetition, and cue-diagnosticity, it analyzes 234 YouTube and Instagram campaigns with 38,774 consumer comments via machine learning-based facial recognition. Results show that social media ads with multiple models outperform single-model ones in driving responses, consistent with theoretical predictions. However, group diversity within ads shows no significant effect. The study offers theoretical, managerial, and methodological insights, highlighting future research opportunities on diversity in advertising.