Sale Forecasting

Sales forecasting aims to predict future sales volumes, crucial for optimizing supply chains and marketing strategies. Current research emphasizes improving forecast accuracy through advanced machine learning techniques, including ensemble methods like Gaussian Processes with Bayesian optimization, gradient boosting machines (like LightGBM), and recurrent neural networks and transformers, often incorporating trend and seasonality decomposition. These models are increasingly being enhanced by integrating diverse data sources, such as incorporating visual data from product images and accounting for external factors like promotions and economic conditions, leading to more robust and accurate predictions with significant implications for businesses across various sectors.