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April 27, 2026Journal of the Academy of Marketing Science3 citationsOpen Access

Free and paid word-of-mouth from physical to digital, AI and beyond

KPKoen PauwelsZAZeynep AksehirliNortheastern University

Key Points

  • This research aims to compare the effects of free and paid word-of-mouth (WOM) on brand performance across digital and physical settings.
  • Integrated 15 years of research and data
  • Developed a conceptual framework for WOM dynamics
  • Examined interplay between free and paid WOM across various product categories
  • Free WOM shows higher trust and authenticity while paid WOM offers greater reach and immediate impact.
  • Differential effectiveness of WOM noted based on product category; some categories benefit more from paid WOM than others.
  • Artificial intelligence enhances WOM strategies in digital and augmented reality environments.

Abstract

Word-of-mouth (WOM) remains one of the most influential drivers of brand success, but its nature and impact have evolved significantly with the evolution of digital platforms and influencers. In the online context, Trusov et al. (2009) explored the effect of non-incentivized, or free WOM on brand performance, finding it to be a powerful and enduring force. However, it lacked the dynamics of paid WOM and the dichotomy between online and offline WOM so prevalent in today’s context. This paper revisits the foundational insights from 2009 to address two critical questions: How does free WOM compare to paid WOM in terms of trust, reach, and impact? And how do online and offline WOM differ in their effectiveness across various product categories? By integrating 15 years of research and data, we aim to provide a comprehensive understanding of these dynamics and suggest areas for future research. To offer actionable insights for practitioners, we suggest a simplified framework that examines the interplay between free and paid WOM, as well as online and offline channels. We combine this conceptual framework with seven urgent practical questions: who, why, which, when, metrics, methods, and magnitude. We highlight how different forms of WOM are suited to specific conditions, balancing authenticity and reach while leveraging category-specific strategies. Artificial intelligence and virtual environments open new frontiers in WOM practice and study. This paper not only extends the theoretical understanding of WOM but also equips marketers with practical tools to navigate the complex landscape of free and paid WOM in physical, digital, and augmented reality environments.

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Cite This Study

Pauwels et al. (2026) studied this question.

synapsesocial.com/papers/69eefd9bfede9185760d44efhttps://doi.org/10.1007/s11747-026-01151-7
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