Modeling User Engagement on Social Media Platforms Through Content Marketing and Personal Branding Using PLS-SEM

In today’s platform-driven digital economy, understanding how content strategies influence user engagement is essential for optimizing online presence. This study models the influence of digital branding elements social media interaction, content marketing, and personal branding on consumer awareness within social media ecosystems. Using a local beauty industry brand as a contextual basis, the research collected responses from 399 users via structured online surveys. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the influence of each factor on user engagement, treated here as a proxy for brand awareness. Results indicate content marketing exerts the strongest effect (β = 0.379), followed by social media interaction (β = 0.239), and personal branding (β = 0.234). These findings provide insight into how user-perceived information quality and emotional authenticity drive engagement within algorithmic platforms such as Instagram. The model demonstrates strong explanatory power (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.554) and contributes to the growing literature at the intersection of digital content systems, behavioral informatics, and data-driven engagement modeling. The implications offer practical guidance for digital marketers, system designers, and platform strategists seeking to optimize interactive features, narrative structure, and influencer integration in social media ecosystems.