LINK/DOI: TBA
28th Pan-Hellenic Conference on Progress in Computing Informatics with International Participation (PCI),
13-15 December 2024, Athens, Greece
Accurate sales prediction is pivotal for optimizing operations and strategic decision-making in the ecommerce sector. This work presents a comprehensive review of existing literature on sales prediction
algorithms, encompassing both traditional statistical approaches and advanced artificial intelligence (AI)
techniques. 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.