AI Smart Cosmetic E-Commerce Platform: Enhanced User Experience and Personalization

 




 

Liew, Qian Wei (2026) AI Smart Cosmetic E-Commerce Platform: Enhanced User Experience and Personalization. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

The AI-Smart Cosmetic E-Commerce Platform aims to revolutionize the online beauty shopping experience by integrating artificial intelligence (AI) to enhance user engagement and personalization. This platform leverages AI-driven cosmetic shade recommendations, providing users with accurate product matches based on their unique skin tones, which minimizes the common issues of mismatched shades in online cosmetic shopping. Additionally, the platform features a robust loyalty program that incentivizes long-term engagement, allowing customers to earn points for purchases, reviews, and referrals. User-generated content, including reviews and ratings, fosters community-driven trust and influences purchasing decisions. The integration of educational makeup tutorials enhances the user experience, offering step-by-step guidance tailored to specific products. This platform is designed to address current gaps in the beauty e-commerce industry by providing a comprehensive, personalized shopping experience, which ultimately promotes customer satisfaction, retention, and brand loyalty. Through its innovative features, the platform aims to set new standards in AI-powered beauty retail by offering a seamless and engaging online shopping environment.

Item Type: Final Year Project
Subjects: Science > Computer Science > Artificial intelligence
Social Sciences > Commerce > Electronic commerce
Technology > Technology (General) > Information technology. Information systems
Faculties: Faculty of Computing and Information Technology > Bachelor of Information Systems (Honours) in Enterprise Information Systems
Depositing User: Library Staff
Date Deposited: 11 Aug 2026 04:11
Last Modified: 11 Aug 2026 04:11
URI: https://eprints.tarc.edu.my/id/eprint/38223