Digital Marketing Budgeting Strategies in Business Management: A Systematic Literature Analysis

Abstract

This systematic literature review (SLR) explores budgeting strategies in digital marketing from a business management perspective. Analyzing 40 peer-reviewed articles published between 2020 and 2025, the study identifies a clear shift toward predictive, performance-based, and customer journey-aligned budgeting models. These strategies leverage data analytics, machine learning, and real-time feedback to optimize financial allocation across digital channels. Findings reveal that effective budget planning enhances ROI, customer lifetime value, and overall marketing efficiency. However, disparities persist due to technological gaps, especially among SMEs and firms in developing regions. Recent innovations, including AI-driven budget automation and omnichannel attribution, offer promising solutions but remain unevenly adopted. This review highlights key theoretical contributions, practical implications, and suggests future research directions, including longitudinal studies, AI integration, and comparative effectiveness analysis across channels. The study provides a foundation for more adaptive, evidence-based budgeting in the evolving digital marketing landscape.