Web-Based Clothing Commerce System (Visual search and Promotion & Reward Modules)

Leow, Zhi Yee (2026) Web-Based Clothing Commerce System (Visual search and Promotion & Reward Modules). Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

Text REI_Leow Zhi Yee_Fulltext.pdf Restricted to Registered users only Download (25MB)

Abstract

This project proposes the development of a brand-owned, web-based clothing commerce system enhanced with AI-powered modules to address common e-commerce challenges such as ineffective product search, impersonal promotions, and low customer retention. The main objective is to improve customer experience and business efficiency through the integration of four core components: a Visual Search Engine for image-based product discovery, a Promotion Module for rule-based personalized discounts, a Reward Module for tier-based loyalty incentives, and a Product Catalog Manager for streamlined filtering, pagination, and inventory visibility. The system leverages object detection and customer behavior analysis to deliver smart shopping interactions that reduce return rates and increase sales conversions. This project complies with the Rapid Application Development (RAD) method, enabling user feedback and iterative prototyping through stages of system design, development, integration, testing, and final deployment. For functionality and reliability purposes, the system undergoes integration testing, user acceptance testing, and final validation. Benchmarking against platforms such as Shein, Zalora, LV and Dior recognizes some of the key areas of visual search and reward strategies, which are improved in the system. Results are expected to show increased customer satisfaction, higher engagement rates, and improved backend operations. In the long term, the solution will empower fashion brands to offer customized and smart shopping experiences, branding the solution as a scalable, cost-effective model for digital transformation in the retail industry.