TY - GEN A1 - Reichstein, Thomas A1 - Brusch, Ines A1 - Dost, Florian A1 - Brusch, Michael T1 - Maximizing Engagement Through Caption Optimization: Insights from Social Media Field Data T2 - 2023 ISMS Marketing Science Conference Proceedings N2 - Social media managers are constantly seeking ways to maximize engagement with their content. While prior research has shed light on strategies for creating engaging content, the impact of captions on engagement has been under-explored. Our study focuses specifically on the relationship between caption length and engagement in social media posts. Contrary to previous literature, we find that the relationship between caption length and engagement follows an inverted U-shape. Using field data from an omnichannel retailer (Facebook) and a travel influencer (Instagram), we determine the optimal caption length for maximizing engagement and present surprising results. Our results are robust for different model and identification specifications, indicating that captions are often too short, rather than too long, and that optimizing caption length in our case can increase engagement by up to 25%. These findings have important implications for social media managers and influencers seeking to enhance the impact of their posts. Y1 - 2024 UR - https://opus4.kobv.de/opus4-UBICO/frontdoor/index/index/docId/33092 UR - https://www.researchgate.net/publication/379237977 ER -