Nonlinear moderating effects of individual social engagement in freemium strategies on digital content platforms

Abstract

PurposeThis study aims to investigate the moderating effects of individual social engagement on the effectiveness of freemium strategies in digital content platforms.Design/methodology/approachThis study involved conducting a randomized field experiment with 74,758 consumers on a prominent e-book platform in China, comparing the effects of offering the first 50 chapters for free against no free content. Additionally, a causal random forest machine learning algorithm was applied to analyze data and optimize strategies based on individual social engagement levels.FindingsThis study indicates freemium strategies on digital content platforms can increase consumer willingness to pay but may reduce social community participation. These effects are moderated by consumers' prior social engagement, with excessive interaction leading to diminishing returns.Practical implicationsThe study offers actionable insights for digital content managers, showing how tailored freemium strategies can effectively balance consumer engagement and revenue generation. The findings suggest that platforms can significantly enhance profitability by moderating free content offerings based on detailed analysis of consumer engagement histories.Originality/valueThis study enhances the understanding of freemium strategies by showcasing their dual impact on consumer willingness to pay and social engagement, and detailing the complex, non-linear effects of individual social engagement, which challenges the traditional linear assumptions in existing literature. Additionally, it provides insights for implementing mixed marketing strategies on digital platforms, where multiple strategies often interact, guiding the effective management of these complexities.