Integrating Evolutionary Computation and Digital Marketing Analytics for Optimization of Complex Business Systems

Abstract

The increasing complexity of modern business systems has created an urgent need for advanced optimization frameworks capable of handling nonlinear, dynamic, and multi-objective decision environments. Two research streams have independently evolved to address these challenges: evolutionary computation in engineering and artificial intelligence, and analytical modeling in digital marketing and customer relationship management. This study develops a comprehensive, theory-driven research narrative that integrates evolutionary computation techniques—particularly genetic algorithms, particle swarm optimization, and differential evolution—with digital marketing analytics, customer acquisition cost optimization, and relationship-based profitability models. Drawing strictly from the provided scholarly references, the article constructs an interdisciplinary framework that explains how bio-inspired optimization methods can be conceptually and methodologically aligned with marketing decision problems such as channel selection, customer retention, affiliate marketing efficiency, and cohort-based CAC payback optimization. The study elaborates extensively on theoretical foundations, methodological assumptions, adaptive learning mechanisms, and strategic implications, emphasizing descriptive explanation rather than mathematical formalization. The findings suggest that evolutionary computation offers a powerful conceptual lens for understanding adaptive decision-making in marketing systems, where uncertainty, competition, and behavioral dynamics dominate. By synthesizing insights from biomimetics, cybernetics, marketing theory, and relationship management literature, this research fills a critical gap between computational optimization and managerial decision sciences. The article concludes that future business optimization will increasingly depend on hybrid models that combine evolutionary intelligence with customer-centric analytics, enabling firms to achieve sustainable competitive advantage in digitally mediated markets.