A Predictive Analytics Framework for Adaptive Marketing Budget Allocation in Volatile Economic Environments
Keywords:
Predictive Analytics, Marketing Budget Allocation, Machine Learning, Economic Uncertainty, ROI Prediction, Data-Driven Decision Making, Forecasting Models.Abstract
This research paper creates a predictive analytics model of adaptive marketing budget allocation, in a situation of uncertain economic conditions. Machine learning models such as Linear Regression, Random Forest, Gradient Boosting and Artificial Neural Networks are used to analyze secondary marketing data and economic data. It has been found out that predictive models are more accurate in conforming with the investment decision-making process, with the Linear Regression having a high R² prediction of 81.4%. The framework identifies the marketing budget and market volatility as significant aspects in optimization of ROI and strategic planning.
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