Design And Development Of A Laravel 13 Based E-Commerce Referral System For Seller Monitoring And Accountability

The rapid growth of electronic transactions necessitates systems capable of monitoring seller quality and reputation across marketplace platforms. This study aims to design and implement a seller referral system on a Laravel 13 based e-commerce platform integrated with performance monitoring and seller accountability mechanisms. Built using the Prototype model encompassing communication, planning, modeling, prototyping, and deployment phases the system utilizes MySQL for database management. Registered sellers can distribute unique referral codes to prospective sellers, with the system automatically recording these relationships to enable structured tracking of activities, product counts, store ratings, and access status of referred sellers. Functional testing conducted via a black-box approach demonstrated that the authentication, referral registration, dashboard, monitoring, order management, and store settings modules operated strictly according to specifications, achieving a 100% test case pass rate. The primary contribution of this research lies in shifting the referral paradigm from simple user acquisition to a peer-accountability framework that holds referring sellers responsible for the performance of their recruits, thereby mitigating the presence of unreliable sellers and fostering greater trust in the online shopping environment.