In the era of digital transformation, marketing activities increasingly rely on data utilization to support more accurate and measurable decision-making processes. PT. Digital Catha Sangkara still faces challenges in determining digital marketing campaign budget allocations because decision-making is often influenced by subjective considerations. This study aims to develop a web-based Decision Support System to support digital marketing campaign budget allocation recommendations. The method applied in this research is the Weighted Product method combined with data normalization to evaluate digital content performance based on several criteria, namely Engagement Rate, Reach, Impression, Profile Visits, and Followers Growth. The data used in this study were obtained from monthly content performance reports and processed to generate preference values and alternative rankings. In addition, campaign budget effectiveness analysis was conducted by comparing the preference values generated by the Weighted Product method with the budget used in each campaign period. The results indicate that the developed system is capable of providing more objective, consistent, and data-driven budget allocation recommendations compared to manual approaches. Furthermore, the effectiveness analysis successfully identified campaign periods that delivered the most optimal performance relative to the budget spent, thereby supporting future campaign evaluation and planning.
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