Neural Network-Enhanced Decision Support: Investigating Prediction Intervals for Real-Time Digital Marketing Return on Investment Data - Morais, Lucas Rabelo de Araujo; Gomes, Gecynalda Soares da Silva (Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), 2024)
This work delves into the application of artificial neural network (ANN) models and recurrent neural networks (RNN), for time-series forecasting in the dynamic realm of digital marketing. Focused on a travel company’s real-time updated Return on Investment (ROI) data from Google Ads campaigns, the research evaluates the efficacy of prediction intervals (PIs) in capturing forecast uncertainties. The study’s contribution lies in the exploration of PIs in ANN models for digital marketing ROI data, providing valuable insights for decision-makers navigating rapidly changing scenarios. The work emphasizes the significance of incorporating intervals in ANN models for robust decision-making in business and digital marketing applications.