THE AI-DRIVEN TRANSFORMATION OF DIGITAL MARKETING: EVOLVING CUSTOMER JOURNEYS, PREDICTIVE ANALYTICS, AND NOVEL ACQUISITION CHANNELS
DOI:
https://doi.org/10.69635/ciai.2026.48Keywords:
Artificial Intelligence; Large Language Models; Digital Advertising; Customer Journey; Predictive Analytics; Campaign Optimization; Customer Acquisition CostAbstract
This study offers an analytical critique of the structural reconfigurations within the digital advertising architecture precipitated by the convergence of machine learning pipelines and Large Language Models (LLMs). By tracing the dissolution of traditional, linear Customer Journeys, the investigation explores how consumer behavior is restructuring around decentralized, conversational inquiry environments. In tandem with examining the economic pressures facing legacy index-based search marketing, this paper introduces a unified programmatic framework developed at ILION DIGITAL that automates cross-channel data ingestion, predictive anomaly diagnostics, and continuous campaign optimization.
Empirical evaluations conducted within hyper-competitive vertical markets across the United States and Ukraine focusing heavily on E-commerce and specialized local services such as Medical, Construction, and Home Services demonstrate that the deployment of unified AI architectures systematically minimizes Customer Acquisition Costs (CAC), prevents rapid budget depletion, and enhances Return on Ad Spend (ROAS). Ultimately, these findings indicate that strategic automation loops do not obsolesce human agency but instead elevate the marketing professional from an operational technician to a core strategic architect.
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Copyright (c) 2026 Vladyslav Bilinchuk, Oleksandr Korogovnyi (Author)

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