AI-Based Consumer Behavior Analytics For Sustainable Marketing Decision-Making

Abstract

The growing emphasis on environmental responsibility has transformed marketing from a purely profit-oriented function into a strategic process that must balance consumer satisfaction, business performance, and sustainability objectives. In this context, artificial intelligence (AI) offers significant potential for understanding complex consumer behavior and supporting more informed and sustainable marketing decisions. This study examines the application of AI-based consumer behavior analytics in identifying consumption patterns, predicting customer preferences, evaluating purchasing intentions, and guiding organizations toward environmentally responsible marketing strategies. AI technologies, including machine learning, predictive analytics, natural language processing, recommendation systems, and sentiment analysis, enable marketers to process large volumes of structured and unstructured consumer data obtained from digital transactions, social media interactions, online reviews, customer feedback, and engagement platforms. By identifying behavioral patterns and emerging preferences, AI can assist organizations in designing personalized marketing campaigns, recommending sustainable products, optimizing promotional expenditure, reducing unnecessary resource consumption, and improving demand forecasting. The study highlights that AI-driven analytics can support sustainable marketing decision-making by enabling firms to better understand consumers’ attitudes toward green products, ethical brands, responsible packaging, energy-efficient services, and environmentally conscious consumption. Furthermore, predictive models can help organizations anticipate demand more accurately, thereby minimizing overproduction, inventory waste, and inefficient distribution practices. Personalized recommendation systems may also encourage consumers to choose products that align with sustainability goals while maintaining relevance to their individual preferences. However, the effective implementation of AI-based consumer analytics requires careful attention to data privacy, algorithmic bias, transparency, consumer trust, and ethical data governance. The study argues that sustainable marketing cannot be achieved solely through technological efficiency; AI systems must be supported by responsible organizational practices and authentic sustainability commitments. Overall, AI-based consumer behavior analytics represents a valuable decision-support mechanism that can help marketers integrate economic objectives with environmental and social responsibility. By converting consumer data into meaningful behavioral insights, organizations can develop more responsive, efficient, ethical, and sustainable marketing strategies, while simultaneously strengthening customer relationships and contributing to long-term sustainable business development.