Image-based brand communications: an information richness approach on Instagram

As a popular brand management practice, firms communicate with consumers using images on social media platforms such as Instagram. Image-based brand communications on social media have two important characteristics. First, brand communications on social media are bilateral, not one-sided as those on traditional media. Second, measuring the information an image delivers is challenging. This study conceptualises a bilateral brand communication model to capture image information exchange between firms and consumers. This research examines how image information generated by firms and consumers changes in such dynamic and dyadic brand communications on Instagram and how brand communication strategies may alter the image information gap between the two parties. This study defines image information richness (IIR) based on information richness theory and applies machine learning techniques to measure IIR through the objective cues present in images. This approach provides brand managers with a practical tool to diagnose and manage their image-based brand communications. Analysis of 10,765 firm-generated images and 6,689 consumer-generated images from eight digital camera brands on Instagram reveals positive dynamic effects but asymmetrical dyadic effects of IIR. Consumer IIR can be inconsistent with firm IIR and thus form an IIR gap.