The convergence of predictive marketing, data-driven marketing and artificial intelligence
strategies, challenges and the future of business
DOI:
https://doi.org/10.12662/2359-618xregea.v14i2.p26-45.2025Keywords:
predictive marketing, Data-Driven Marketing (DDM) , artificial intelligence (AI), AI ethics, Big Data in marketing , Intelligent Strategic CycleAbstract
This paper investigates the convergence between predictive marketing, Data-Driven Marketing (DDM), and artificial intelligence (AI), highlighting how this integration reshapes marketing strategies and business management. The research highlights the benefits of this approach, such as the personalization of consumer experiences, the predictability of market behaviors, and operational efficiency, with practical examples of companies such as Netflix and Amazon, which use algorithms to engage and retain customers. In addition, the study addresses the adoption of DDM in sectors such as retail and healthcare, where it becomes a competitive differentiator. However, implementing these technologies faces significant challenges, including the need to ensure data quality, overcome cultural barriers, and comply with regulations such as the LGPD and GDPR. Ethical issues, such as algorithmic bias and concentration of information, are also discussed, underscoring the importance of a responsible approach. The paper concludes that the future of predictive marketing and DDM is promising, with emerging technologies such as explainable AI, quantum computing, and the Internet of Things (IoT) expected to extend personalization and prediction capabilities. Collaboration between business, government, and academia is considered essential for the development of ethical practices. In short, integrating these tools represents a structural transformation that redefines the use of data and technology, with significant potential to impact industries and public policies.
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