Tracking Barista Productivity and Customer Demographics

This research presents a comprehensive approach for management of coffee shops by tracking the barista productivity and customer demographics. The use of data analysis tools and computer vision techniques provides the owner of coffee shops with important data for escalating sales. By leveraging OpenCV on surveillance systems the number of cups served by each barista are measured accurately. Using os, datetime, imultis and numpy libraries the operations related to directory manipulations, time tracking, image processing and numerical calculations are performed. In addition to tracking barista productivity, the purpose is to track customer demographics that include gender, age, and the duration of their visit. The collected data is analyzed using R, utilizing various graphical representations to provide insightful visualizations. This allows the coffee shop owner to perform detailed analyses based on multiple parameters, offering a granular view of operational efficiency and customer behavior. The integration of these technologies not only aids in identifying trends and patterns but also empowers decision-making processes to optimize service quality and customer satisfaction. This methodology serves as a robust framework for other coffee shops aiming to enhance their operational strategies through data-driven insights