Using Machine Learning to Optimize Green Influencer Marketing Strategies: A Study of Consumer Behavior Trends

Neetu, Sharma (2025) Using Machine Learning to Optimize Green Influencer Marketing Strategies: A Study of Consumer Behavior Trends. Journal of Business and Social Sciences, 2025 (06). pp. 1-16. ISSN 2805-5187

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Abstract

In the backdrop of increasing sustainability awareness among Indian consumers, this study explores the role of machine learning (ML) in optimizing green influencer marketing strategies to drive eco-conscious purchasing. While eco-friendly consumer behavior and influencer marketing have gained traction, there remains limited empirical evidence on how ML-enabled recommendation systems can enhance green influencer effectiveness in India. Employing a quantitative research design, data were gathered through surveys of 1,500 users of an Indian e-commerce platform. Respondents provided insights on their interactions with green influencers, their perceptions of influencer authenticity and transparency, and the impact of ML-driven recommendations on purchase intent. Factor and correlation analyses examined the relationships among perceived authenticity, consumer trust, and purchase behavior. Findings reveal that influencer trustworthiness, particularly authenticity and transparency, significantly drives consumer engagement with green products. Most respondents expressed willingness to purchase green products when the messaging was authentic and well-targeted. Moreover, ML algorithms were instrumental in identifying top-performing influencers, segmenting audiences by green preferences, and personalizing recommendations, which enhanced engagement and conversion rates. Positive correlations were observed between influencer authenticity, trust, and purchase intention. This study fills a regional gap by offering India-specific, empirical evidence on the synergy between ML-driven marketing and green consumer behavior. Its practical implications are twofold: marketers can leverage these insights to enhance influencer selection and recommendation strategies, while policymakers and researchers gain a data-informed perspective to promote sustainable marketing practices. The study demonstrates that ML-augmented green influencer marketing can effectively elevate sustainability and commercial performance within the Indian e-commerce context.

Item Type:	Article
Uncontrolled Keywords:	Machine learning, green marketing, influencer marketing, consumer behaviour, sustainability, data-driven strategies
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HF Commerce
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	09 Sep 2025 09:58
Last Modified:	09 Sep 2025 09:58
URI:	http://eprints.intimal.edu.my/id/eprint/2175

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