Optimizing Customer Targeting and Pricing through Causal Inference, Machine Learning, and Artificial Intelligence

Abstract

The increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) into marketing heralds a new era of digital transformation. As businesses capitalize on technological advances to digitize offline consumer behavior and enhance data-driven marketing strategies, the importance of brand influence in premium sectors such as automotive becomes pivotal. This research explores how AI and ML revolutionize traditional marketing practices, offering precise customer targeting and pricing optimization. By employing causal inference methods, this study provides insights into the decision-making processes of consumers and managers, emphasizing the freedom of choice and improved judgments in utilizing algorithmic predictions over human forecasters. We propose a three-stage framework to utilize AI in marketing research, strategy development, and action, showcasing how 'thinking' and 'feeling' AI can dramatically enhance customer relationship management and marketing personalization.