Personalized Digital Marketing for Sustainable Consumer Behaviour: A Study on E-Commerce Platforms, Customer Engagement, and Green Consumption Practices

Subject area: Computer Science DOI: https://doi.org/10.5281/zenodo.21126685

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Abstract

AI-based personalization is changing the way customers interact with online shopping platforms, but it is important that these developments also support environmental sustainability. This study examines how personalization techniques such as recommendation systems, data analysis, and language-based tools can encourage customers to make eco-friendly choices, reduce unnecessary purchases, and minimize product waste. The research focuses on how personalized shopping experiences can promote sustainable buying habits, lower product returns, and support a circular economy.
Using a mixed-method approach, the study analyzes case studies of digital platforms that combine personalized customer experiences with sustainable practices. These platforms are evaluated based on important factors such as customer engagement, purchase behavior, reduction in environmental impact, and improvement of product lifecycle management. Although personalization offers several advantages for sustainable e-commerce, challenges related to data privacy, fairness, and responsible use remain. The study emphasizes the need for responsible and environmentally conscious approaches that provide better customer experiences while supporting long-term sustainability goals.

Keywords

Personalized shoppingSustainable consumer behaviorE-commerce marketingDigital platformsGreen consumptionSustainable marketing

Cite this article

G Ravinder, G.SWATHI REDDY, Dr. B. RAVI KUMAR (2026). Personalized Digital Marketing for Sustainable Consumer Behaviour: A Study on E-Commerce Platforms, Customer Engagement, and Green Consumption Practices. International Innovations & Scholarly Trends Journal, 2(6), 4221–4238. https://doi.org/10.5281/zenodo.21126685

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© 2026 — Authors retain the copyright of this article. This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.