The Role of Quantum Machine Learning in Optimizing Neuromarketing Insights for Retail and E-Commerce

Abstract

Neuromarketing combines neuroscience and traditional marketing to uncover the emotional and cognitive drivers behind consumer behavior. As retail and e-commerce sectors increasingly rely on customer data for personalized experiences, the complexity of large datasets often surpasses classical machine learning capabilities. This gap allows Quantum Machine Learning (QML) to emerge as a transformative solution, enhancing predictive power and efficiency in neuromarketing. QML improves data processing speed and pattern recognition, enabling companies to gain deeper insights into consumer preferences and engage customers more personally. This chapter evaluates QML's applications in retail and e-commerce, highlighting how quantum algorithms can overcome current AI limitations regarding speed and precision. It also addresses data privacy concerns, emphasizing ethical data handling practices to foster consumer trust. Ultimately, the chapter envisions QML as a pivotal technology that will redefine consumer engagement and optimize marketing strategies in an increasingly data-driven landscape.