Abstract

Visual-based social media are growing exponentially and have become an integrated part of the customer engagement strategy of many brands. Prior work points to the textual message content as a driver of customer engagement behavior. So far, little is known about the impact of visual message content, specifically visual emotional and informative appeals. We extract emotional and informative appeals from Instagram posts using machine learning models and use a Negative Binomial model to explain customer engagement. We test our model on 46.9 K Instagram posts from 59 brands in six sectors. Our results show that visual emotional and informative appeals encoded in brand-generated content influence customer engagement in terms of likes and comments. Specifically, we demonstrate that positive high and negative low arousal images drive customer engagement. Informative appeals do not drive customer engagement with the exception of informative brand-related appeals. These findings help brand managers in developing an effective customer engagement strategy on visual social media.

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