A Proposed Nonlinear Programming Optimization Model for Optimal Budget Mix of Digital Marketing Campaigns

Abstract

This paper proposes a nonlinear mathematical model to address the problem of optimizing budget allocation within digital marketing campaigns. The model provides marketers with a systematic quantitative framework for effective budget allocation across various platforms. The model seeks to identify the optimal budget mix that maximizes the expected net impressions using the Sainsbury Normal Method (SNM). The proposed model considers multiple constraints, such as budget limitations and advertiser's preferences. Results demonstrate the applicability of the model through hypothetical two case studies and scenario analysis. Furthermore, the model allows marketers to incorporate real-time data and adjust parameters based on the ongoing campaign's characteristics, audience, and advertiser's preferences.