Optimizing Marketing ROI with Predictive Analytics: Harnessing Big Data and AI for Data-Driven Decision Making

Authors

  • Sofia Lopez Research Scientist, Healthcare Informatics Lab, Andes University, Bogota, Colombia
  • Gopalakrishnan Arjunan AI/ML Engineer at Accenture, Bangalore, India

Keywords:

Predictive analytics, Artificial intelligence, Marketing ROI, Data-driven decision-making, Customer behavior forecasting

Abstract

This paper explores the synergy between predictive analytics, big data, and artificial intelligence (AI) in revolutionizing marketing strategies for Industry 4.0. By harnessing advanced analytics techniques, organizations can predict customer behavior, enhance marketing campaigns, and allocate resources efficiently to amplify return on investment (ROI). The study delves into the methodologies of predictive analytics and AI algorithms, showcasing their applicability in deciphering vast datasets to extract actionable insights. Through case studies and examples, we illustrate how companies across various industries are leveraging these technologies to gain a competitive edge in the dynamic marketplace of today. Furthermore, the paper discusses the challenges and ethical considerations associated with implementing predictive analytics and AI in marketing practices. Overall, this research underscores the pivotal role of data-driven decision-making in optimizing marketing ROI in the era of Industry 4.0.

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Published

01-12-2023

How to Cite

[1]
S. Lopez and G. Arjunan, “Optimizing Marketing ROI with Predictive Analytics: Harnessing Big Data and AI for Data-Driven Decision Making”, J. of Art. Int. Research, vol. 3, no. 2, pp. 9–36, Dec. 2023.

Issue

Vol. 3 No. 2 (2023): Journal of Artificial Intelligence Research

Section

Articles

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