AI-Infused Personalization: A Catalyst for Transforming the Retail Marketing Mix (4A)

Abstract

In the era of digitalization, evolving customer needs influence purchasing behavior and pricing dynamics, prompting adaptations in the marketing operational model (Davenport et al., 2019; Stone et al., 2020; Lasi, 2021; Gołąb-Andrzejak, 2023), facilitated by emerging Artificial Intelligence (AI) technologies (Kumar et al., 2021). AI, defined as a suite of software tools emulating human-like cognitive abilities, extends beyond robotics, significantly influencing daily life (Kumar et al., 2019). Due to limited studies on AI’s impact on the marketing mix (Stone et al., 2020; Lasi, 2021; Nanayakkara, 2020), a research gap persists in exploring new marketing mix models considering AI-enabled tools and processes. This paper, based on the analysis real-case examples, investigates the transformative impact of Artificial Intelligence (AI) on marketing strategies, providing a conceptual model, and highlights the pervasive integration of AI in marketing strategies, reshaping the traditional marketing mix (Nanayakkara, 2020). Emphasizing AI’s role in strengthening customermarketer connections through personalized marketing, with a focus on segmentation, targeting, and positioning decisions (Huang & Rust, 2021), the study positions the traditional marketing mix (Product, Price, Place, and Promotion or 4Ps) as a foundation. The paper contends that AI-driven personalization transforms the marketing mix into a dynamic system termed 4A: AI-Advanced Offerings, Adaptive Pricing, AI-driven Distribution Networks, and Aligned Marketing Approaches. Acknowledging the evolving AI and marketing landscape (Stone et al., 2020), the study provides insights for scholars and practitioners.