Keywords
retail marketing
marketing ROI
budget optimization
customer retention
cross-functional alignment
cash flow forecasting
artificial intelligence in retail
United States
South Korea
Central Europe
How to Cite
Abstract
This study investigates how predictive financial artificial intelligence (AI) enhances retail marketing performance by enabling tighter alignment between financial forecasting and marketing decision-making. Drawing on a comparative multi-case analysis of retail organizations operating in the United States, South Korea, and Central Europe, the paper explores how AI-generated cash flow, margin, and retention forecasts are used to inform budget planning, campaign design, and customer retention strategies. The findings reveal that predictive financial AI is not only a tool for efficiency but also a catalyst for cross-functional coordination. In the U.S. context, financial AI enables real-time budget reallocation and campaign optimization based on projected ROI and CAC thresholds. In South Korea, firms use AI to evaluate the cost-effectiveness of personalized retention offers based on LTV simulations. In Central Europe, early-stage adoption shows promising improvements in margin control and marketing accountability. The study contributes to the literature on finance–marketing alignment by introducing a conceptual model of finance-informed marketing strategy enabled by AI. It also offers practical guidance for global retailers seeking to integrate financial forecasting tools into marketing workflows. As predictive technologies become more prevalent, such integration will be critical to building organizational resilience and marketing precision in volatile and competitive environments. These results offer not only empirical evidence but also a forward-looking perspective on how finance and marketing teams can co-evolve through AI adoption to improve decision-making, performance metrics, and strategic agility in a data-driven economy. The paper underscores that AI does not replace human expertise but strengthens it by improving visibility into financial risks and marketing potential. This integration of financial and marketing logic, supported by shared dashboards and AI-based forecasting, fosters transparency, accountability, and better strategic planning across functions. Ultimately, the research highlights the emerging role of finance as a co-architect of marketing effectiveness in the age of artificial intelligence.
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