THE IMPACT OF MACHINE LEARNING ON PROMOTIONAL STRATEGIES: A STUDY OF AI-POWERED COUPON PERSONALIZATION

Authors

  • Anandkumar Kumaravelu Dell Technologies Inc, USA Author

Keywords:

Machine Learning, Personalization, Customer Data Analytics, Targeted Marketing, Data-Driven Marketing

Abstract

This article examines the transformative impact of artificial intelligence (AI) and machine learning algorithms on coupon personalization strategies in digital retail environments. By analyzing vast amounts of customer data, including purchase history, browsing behavior, and demographic information, AI-powered systems can create highly targeted and personalized coupon offers. This article investigates the effectiveness of these AI-driven approaches compared to traditional coupon distribution methods, focusing on key performance indicators such as customer engagement, conversion rates, and overall sales impact. Through a mixed-methods approach combining quantitative analysis of transaction data from major e-commerce platforms and qualitative insights from industry experts, we demonstrate that AI-powered personalization significantly enhances the relevance of promotions to individual customers. Our findings reveal a 37% increase in coupon redemption rates and a 22% boost in customer retention for businesses implementing AI-personalized coupon strategies. However, the article also addresses critical challenges, including data privacy concerns, algorithm bias, and the need for transparent AI decision-making processes. This article contributes to the growing body of literature on AI applications in marketing and provides practical insights for retailers seeking to leverage AI for more effective promotional strategies in an increasingly competitive digital marketplace

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Published

2024-09-11

How to Cite

Anandkumar Kumaravelu. (2024). THE IMPACT OF MACHINE LEARNING ON PROMOTIONAL STRATEGIES: A STUDY OF AI-POWERED COUPON PERSONALIZATION. INTERNATIONAL JOURNAL OF ENGINEERING AND TECHNOLOGY RESEARCH (IJETR), 9(2), 168-176. https://lib-index.com/index.php/IJETR/article/view/IJETR_09_02_015