How Does Brand-Generated Content Engage Consumers? A Study on Fashion Brands’ Instagram Data

Abstract

Brand-generated content has become one of the most popular marketing strategies for brands to influence consumers’ attitudes and purchase intentions. Faced with intense competition on social media, brands must understand how to design posts to maximize engagement. In particular, fashion brands are highly active on social media platforms to communicate with audiences and drive more web traffic. In this research, the authors analyze Instagram posts from major fashion brands to measure the effects of post design variables on the number of likes. They extract design features of posts using machine learning techniques and use Poisson regression to measure the impacts of these features on user engagement. Among the findings is that inserting URLs in Instagram posts is unattractive to users, but adding more images in the same post is generally effective. Meanwhile, the findings show distinct effects between luxury and mass-market brands. For instance, luxury brand audiences prefer posts that focus on products without distractions such as influencers and conspicuous backgrounds. In contrast, mass-market brand audiences engage more with posts featuring celebrity influencers and appealing backdrops. This research contributes to the growing social media literature by adding a practical methodology to measure the effects of Instagram design variables on user engagement.