Visual Gestures in Digital Advertising From Analysis to Application

This is a study on the effects of visual gestures on audience engagement in digital advertising. Digital advertisements are becoming more interactive, increasingly employing hand motion, facial expressions, and body gestures to attract consumer attention, instead of just eye gaze, and increasing consumer engagement. Using machine learning, the framework extracts user response data from advertisements to analyze the effectiveness of visual gestures in the ads. Using machine learning models, the team analyzed a dataset of gesture-based and non-gesture-based advertisements for audience interaction, emotional engagement, and brand recall. The findings show that ads containing visual gestures outperform static ads across all three measures. The gestures were fluid and therefore attracted more attention and interaction which increased engagement rates. The emotional responses were significantly higher as gestures enabled the audience to connect with the ad content at a greater level. Brand recall rates also increased, which speaks to the power of visually expressive ads to create lasting associations. This emphasizes the scope of gesture analysis in aiding advertisement techniques and content effectiveness options.