Assessing The Effectiveness of Tiktok-Based Digital Marketing Communication: A Social Media Analytics Study of Consumer Engagement
Abstract
This research aims to assess the effectiveness of TikTok-based digital marketing communication by examining consumer engagement through a Social Media Analytics (SMA) approach. The study addresses a research gap concerning the limited use of Social Media Analytics to examine TikTok as an integrated digital marketing communication ecosystem in emerging markets. In the Industry 4.0 era, the rapid shift from text-based communication to short-form video content has transformed the way brands interact with consumers. TikTok has emerged as a dominant social media platform due to its interest-based algorithm, which enables content dissemination beyond conventional follower-based networks. This study employs a qualitative research design grounded in the perspectives of digital marketing communication and consumer engagement, this study employs a qualitative Social Media Analytics approach utilizing Social Media Analytics to analyze engagement indicators, including views, likes, comments, shares, and user-generated interactions within selected viral marketing campaigns in Indonesia. Data were collected through digital observation and discourse analysis of 36 purposively selected publicly accessible TikTok marketing videos uploaded by verified brands, business accounts, and Key Opinion Leaders (KOLs) in Indonesia between January and March 2026. The selected content met predefined inclusion criteria based on marketing relevance, audience engagement, and public accessibility.. The findings reveal that TikTok marketing communication effectiveness emerges from the interaction between algorithmic visibility, authentic storytelling, influencer credibility, and participatory audience engagement rather than from isolated promotional activities. Interactive platform features including challenges, duets, and stitches further strengthen consumer participation by encouraging user-generated communication and content diffusion.
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Copyright (c) 2026 Adam Bergas Prayuda, Ahmad Syuheri, Suroso, Zairil Hakim
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