THE APPLICATION OF FRACTAL THEORY IN MARKETING: WHAT CAN WE DO?

Fractal theory has emerged as a powerful mathematical tool for analyzing complex, nonlinear, and self-similar patterns across various business and engineering domains. This review explores the role of fractals in enhancing decision-making and predictive capabilities within five key application areas: consumer segmentation, demand forecasting, inventory optimization, financial market prediction, and logistics and distribution planning. We highlight how fractal-based methods — such as fractal dimension, multifractal analysis, and entropy measures — can be integrated with machine learning to improve pattern recognition, uncertainty quantification, and system adaptability. Specific attention is given to explainability, data granularity, and the synergy between fractal modeling and AI frameworks. Key challenges and limitations, including model interpretability and computational complexity, are also discussed, along with future research directions aimed at making fractal analytics more actionable in business environments.