Following trends on social media has become increasingly popular. But what is the best way to do so? Should brands and other creators copy the trend as closely as possible, or should they put a more unique spin on it? To answer this question, the authors develop a multimodal, unsupervised video analytics tool (MUVID) to quantify the typicality of over 85,000 TikTok dance videos. Results indicate that more atypical videos (i.e., more differentiated from the trend) generate more engagement. Consistent with the notion that atypicality drives engagement, this relationship is amplified when atypicality is easier to observe (i.e., when audiences have seen more trend videos). Follow-up experiments, including a content-creator field experiment, manipulate atypicality and confirm its causal impact. The findings provide practical guidance on how to create more impactful content, shed light on effective trend-following, and offer a tool (available through an app) that researchers and practitioners can use to quantify typicality and analyze short videos more generally.