A real world case study on sales prediction using Artificial Intelligence

Accurate sales prediction is pivotal for optimizing operations and strategic decision-making in the e-commerce sector.This work presents a comprehensive review of existing literature on sales prediction algorithms, including both traditional statistical approaches and advanced artificial intelligence (AI) techniques.By utilizing a dataset from a major online retailer in Greece, we apply several AI-driven models to forecast sales performance.Our preliminary results demonstrate the efficacy of AI algorithms in capturing complex patterns within the data, leading to improved prediction accuracy over conventional methods especially when semantic data from exogenous sources, e.g.weather and Google Trends are incorporated.These findings underscore the potential of integrating AI into sales forecasting to enhance the competitiveness and efficiency of e-commerce businesses.