ChatGPT Supported Interpretation on Anomaly Detection in Retail Data and Exchange Rate Relationship

Anomaly detection is used effectively in the retail sector to enhance operational efficiency and inform strategic decision-making processes. This study identifies anomalies in total sales figures within retail data and examines their relationship with exchange rates. Subsequently, the causes of these anomalies were investigated by querying ChatGPT, an artificial intelligence-supported system, and explanations were provided based on significant events occurring on the relevant dates. The analyses demonstrated that identifying anomalies early allows businesses to quickly assess the reasons for these changes and develop appropriate strategies. This study makes a significant contribution to the literature by highlighting how anomaly detection can help minimize risks and capitalize on opportunities within the retail sector