Nudging consumer engagement for food brands: a machine learning and visual framing-based typological approach

Purpose This study aims to investigate how visual content strategies influence consumer engagement with food brands on Instagram by developing a post typology, examining its engagement effects and analysing the moderating role of post modalities through the lens of Nudge and Media Richness Theory. Design/methodology/approach Instagram posts from food brands were analysed using machine learning techniques and visual framing methodology, and operationalised as post typologies. The impact of post typologies and modalities on consumer engagement was analysed using negative binomial regression. Findings The study reveals that post orientations, such as socioemotional and post typologies, like infotainment and transformational, significantly enhance consumer engagement. Video content proved more effective for socioemotional-oriented, interactional and transformational posts, whereas image was more effective for task-oriented and infotainment posts. Practical implications By understanding the interplay between post orientations, typologies and modalities, this study offers actionable insights for brands to create compelling content that drives consumer engagement and encourages informed food choices, enabling food brands to take a proactive role in shaping consumer preferences. Originality/value Unlike prior research that primarily used content analyses, this study develops four post typologies grounded in established frameworks: one-way and two-way communication and interaction process analysis. By integrating Nudge and Media Richness theory and introducing post modality as a moderator, it offers a novel perspective on how content type and modality together influence consumer engagement on social media.