In this study, we developed a deep learning-based customer forecasting tool to improve the management quality of decision making. The proposed approach extracted the relationship between the number of customers and leading factors of huge amount of historical data. The conducted leading factors provide innovative approaches to adjust the manage settings regarding the labor arrangement strategies. In particular, the Point of Sale (POS) data was collected. Deep Learning were utilized to execute significant sales analysis and produce reliable predictions that would become administrative tools, especially with the building of a forecasting model based on customer behavior with weather as the prediction parameter. As a result of the information obtained by this research, recommendations concerning the pharmacy's administration were made, understanding the usefulness of basing the study on the customers. The deep learning-based customer forecasting tool can be used on different industries, which broadens the future work of this research.
['Kuo-Yi Lin', 'Jeffrey J.P. Tsai']
A Deep Learning-Based Customer Forecasting Tool