AI-Driven Insights for Sustainable FMCG Marketing: Understanding Purchase Intention of Organic Consumers in Karnataka

DOI: https://doie.org/10.10399/ES.2025128185

Rashmi K M, Rakesh N, Shobha B K, Netravathi N

Keywords:

Sustainable Marketing, Artificial Intelligence, Customer Experience, Organic FMCG, Purchase Intention, Structural Equation Modelling.

Abstract:

As sustainability becomes a major part of consumer attitudes, artificial intelligence (AI) is also reshaping the landscape of marketing strategies. In this context, organizations possess a large and consonant opportunity in their hands to strategically combine these two potent elements to build a competitive advantage in the marketplace. This current research is carried out with the very specific objective of empirically testing different aspects of sustainability marketing and their effects. This involves a thorough analysis of significant variables like carbon foot printing labeling, ethical sourcing initiatives, and green packaging innovations for packaging, i.e., their effects on consumer buying intentions of organic fast-moving consumer goods (FMCG) in Karnataka state of India. In addition, this research also seeks to determine how customers' experience assets augmented by artificial intelligence, such as customized product recommendations, chatbot-supported customer care for query resolution, and sophisticated predictive analytics for forecasting consumer behavior, act as mediating and moderating variables in the impact of sustainable marketing on consumer decision-making processes.

The research design used in this study will predominantly be quantitative in nature, which is a prevalent scientific method appropriate for systematic data analysis. Specifically, this study will employ a highly structured questionnaire carefully crafted, which is an instrumental device for the acquisition of accurate and appropriate information from a representative sample of consumers. The sampling will be conducted in a manner to reflect a broad spread of demographic profiles, thereby achieving a broad representation across Karnataka state. On completion of data collection, data will be analyzed using Structural Equation Modeling (SEM), which is a highly versatile statistical technique that enables estimation and disclosure of hypothesized relationships between a set of meaningful variables. These variables encompass some aspects of sustainability, customer experience enhanced through artificial intelligence (AI), trust in AI, and lastly, consumers' buying intentions. Moreover, the theoretical framework of this research will consider the effect of consumer trust in artificial intelligence (AI) as a moderating variable on the interaction between personalized AI experiences and actual buying behaviors of these consumers.

The study will be compelled to probe very deeply into the wide range of psychological and experiential channels through which green marketing, enabled by the innovative capacity of artificial intelligence, can strongly shape and even augment the key elements of customer loyalty, trust, and buying behavior. For this, it will attempt to graphically depict the many ways through which customer experience can serve as a strategic connective bridge of significant value between green brand campaigns and consumer behavior, especially in an increasingly technology-mediated retail environment. In addition, the study will also not hesitate to explore significant ethical concerns stemming from the use of AI, such as issues related to data privacy, possible algorithmic biases, and process transparency. Through active participation in the forecasting process and cautious consideration of these possible scenarios, the study aims to make an important and significant contribution to the growing and increasingly relevant body of literature regarding sustainable consumer attitudes, an emerging and increasingly significant subdiscipline of digital marketing, as well as to the highly consequential issue of AI ethics. The findings and conclusions of this study will be of specific value and inherent significance to marketers, retail managers, and policymakers who are working to effectively design and manage coordinated campaigns that account for environmental attitudes while cautiously weighing them against state-of-the-art solutions that give primacy to consumer experience. This study will also provide critical data that will be a guiding framework for the regulation of AI in relation to sustainable retail practice, with actionable recommendations and practical recommendations designed to facilitate responsible adjustments in marketing strategy in response to the multi-faceted challenges of the age of artificial intelligence.

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