Product Management System with Analytics

Ooi, Chew En (2022) Product Management System with Analytics. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

TARUC convenience store currently has no system to manage the online convenience store. If the TARUC online convenience store goes live, it will require the store owner and employees to manually process online orders which is troublesome and human errors may occur. As brick-and-mortar convenience stores follow business hours, the store owner cannot check orders anytime, anywhere. Therefore, our developers decided to develop a Product Management System to allow the store owner and employees to manage online convenience store in more efficient way. We believe that the store owner and staffs can benefit from using this system as it reduces human error, improves time efficiency, while also bringing convenience and 24/7 accessibility. The system includes function such as order management, customer management, product management, login authentication, dashboard, admin and profile management. Best of all, it integrates with Firebase Analytics tools, allowing store owners to track customer footprints and understand their preferences. The waterfall methodology is applied when developing this system. The main benefit of using it is that roles and responsibilities are clear, i.e. I will be responsible for the management side and my teammates will be responsible for the client-side. Our developers performed a variety of system tests, including unit testing, integration testing, and acceptance testing to ensure that the results of the system meet our expectations. A total of 97 test cases were performed, and 92.5 of the 97 test cases were as expected in unit testing. The system is cost-effective as we’re using free services such as Cloud Firestore, Cloud Storage and Firebase Analytics. However, some improvements are needed, such as importing analytics results from Firebase, and improving the user interface for compatibility with different devices to enhance the user experience. In conclusion, the Product Management System with Analytics is high reliable and has high potential