Revolutionizing Retail Analytics: Advancing Inventory and Customer Insight with AI

arXiv:2405.00023v1 Announce Type: new
Abstract: In response to the significant challenges facing the retail sector, including inefficient queue management, poor demand forecasting, and ineffective marketing, this paper introduces an innovative approach utilizing cutting-edge machine learning technologies. We aim to create an advanced smart retail analytics system (SRAS), leveraging these technologies to enhance retail efficiency and customer engagement. To enhance customer tracking capabilities, a new hybrid architecture is proposed integrating several predictive models. In the first stage of the proposed hybrid …

abstract advanced aim analytics arxiv challenges create cs.cv customer demand demand forecasting edge forecasting insight inventory machine machine learning management marketing paper queue retail retail analytics sector smart technologies type