The Analysis of Customers’ Transactions Based on POS and RFID Data Using Big Data Analytics Tools in the Retail Space of the Future

In today’s business landscape, the volume of transaction data is rapidly increasing. This study explores the integration of Point of Sale (POS) and Radio-Frequency Identification (RFID) technologies to enhance the analysis of customer transactions using big data tools. By leveraging these technologies, businesses can extract valuable insights to improve processes, optimize inventory, and boost customer satisfaction. The research employs an object—subject management approach, which facilitates real-time decision-making by merging retail transactions of the clients with their movement patterns. An experiment involving around 7000 customers demonstrates the effective collection and processing of POS and RFID data, highlighting the benefits of integrating these data streams. Key metrics, such as time spent in different store sections, provide deeper insights into consumer behavior. The findings reveal the potential of these technologies to transform retail services, offering opportunities for demand forecasting, risk management, and personalized customer experiences. The study concludes that merging POS and RFID data opens new avenues for developing management solutions aimed at enhancing customer engagement and the operational efficiency of the retailer. Future research will focus on further elaborating these solutions to maximize the benefits of integrated data analysis.