AI-Driven Growth Levers for Direct-to-Consumer Marketing Businesses
DOI:
https://doi.org/10.22399/ijcesen.5177Keywords:
Artificial Intelligence, Direct-to-Consumer Marketing, Customer Lifetime Value, Revenue Growth, Predictive Analytics, Retention IntelligenceAbstract
The rapid expansion of direct-to-consumer (DTC) marketing businesses has intensified the need for scalable, data-driven growth strategies. This study examines how artificial intelligence (AI) functions as a multidimensional growth lever within DTC ecosystems by integrating acquisition intelligence, personalization intelligence, operational intelligence, and retention intelligence. Using a quantitative explanatory design, data from 120 DTC firms were analyzed through Random Forest modeling, Structural Equation Modeling (SEM), canonical correlation analysis (CCA), and dynamic growth simulations. The results reveal that retention intelligence exerts the strongest influence on revenue growth, primarily through its significant impact on customer lifetime value (CLV), which mediates the relationship between AI capabilities and financial performance. Acquisition intelligence significantly improves conversion efficiency and reduces customer acquisition cost, while personalization intelligence enhances CLV through targeted engagement. Operational intelligence contributes to margin expansion and supply chain efficiency. Scenario-based simulations demonstrate compounding growth trajectories under high AI adoption intensity, indicating nonlinear and widening performance advantages over time. Canonical correlation analysis confirms systemic alignment between AI maturity and multidimensional growth outcomes. The study concludes that AI-driven growth in DTC marketing businesses depends on integrated capability deployment rather than isolated technological adoption, positioning AI maturity as a structural determinant of scalable and sustainable competitive advantage.
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