Digital assistant for E-commerce website
Due to the Covid-19 pandemic, the popularity of online shopping has skyrocketed, with more people opting to buy everything from groceries to luxury items online. As a result, electronic commerce is becoming increasingly popular in Malaysia. This project aims to identify the problems and weaknesses o...
| Main Author: | |
|---|---|
| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2023
|
| Subjects: | |
| Online Access: | http://eprints.utar.edu.my/5530/ http://eprints.utar.edu.my/5530/1/fyp_IA_2023_CJW.pdf |
| _version_ | 1848886438741934080 |
|---|---|
| author | Chuah, Wenn Jing |
| author_facet | Chuah, Wenn Jing |
| author_sort | Chuah, Wenn Jing |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | Due to the Covid-19 pandemic, the popularity of online shopping has skyrocketed, with more people opting to buy everything from groceries to luxury items online. As a result, electronic commerce is becoming increasingly popular in Malaysia. This project aims to identify the problems and weaknesses of four of the most popular e-commerce websites in the country: Shopee, Lazada, Zalora, and Padini. Utilizing artificial intelligence (AI) technology, this project seeks to address the problems currently faced by these e-commerce websites. Specifically, the project will address three major issues: time wasting when seller want to perform repetitive operations of add a new product or modify the information of existing product, limitations on product filtering features that hinder users' ability to find the desired product, and the complexity of the websites due to multiple features that require users to spend more time and effort to navigate. To address these issues, AI-powered and non-AI-powered digital assistant will be developed to act as a virtual personal assistant for users. This assistant will provide users with quick shopping guides, effective filter criteria, quick search, and hot recommendation functionality. By integrating the digital assistant into the e-commerce website, the user experience will be improved, making online shopping easier and more enjoyable. |
| first_indexed | 2025-11-15T19:38:30Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-5530 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:38:30Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-55302023-08-18T08:30:46Z Digital assistant for E-commerce website Chuah, Wenn Jing T Technology (General) Due to the Covid-19 pandemic, the popularity of online shopping has skyrocketed, with more people opting to buy everything from groceries to luxury items online. As a result, electronic commerce is becoming increasingly popular in Malaysia. This project aims to identify the problems and weaknesses of four of the most popular e-commerce websites in the country: Shopee, Lazada, Zalora, and Padini. Utilizing artificial intelligence (AI) technology, this project seeks to address the problems currently faced by these e-commerce websites. Specifically, the project will address three major issues: time wasting when seller want to perform repetitive operations of add a new product or modify the information of existing product, limitations on product filtering features that hinder users' ability to find the desired product, and the complexity of the websites due to multiple features that require users to spend more time and effort to navigate. To address these issues, AI-powered and non-AI-powered digital assistant will be developed to act as a virtual personal assistant for users. This assistant will provide users with quick shopping guides, effective filter criteria, quick search, and hot recommendation functionality. By integrating the digital assistant into the e-commerce website, the user experience will be improved, making online shopping easier and more enjoyable. 2023-01 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/5530/1/fyp_IA_2023_CJW.pdf Chuah, Wenn Jing (2023) Digital assistant for E-commerce website. Final Year Project, UTAR. http://eprints.utar.edu.my/5530/ |
| spellingShingle | T Technology (General) Chuah, Wenn Jing Digital assistant for E-commerce website |
| title | Digital assistant for E-commerce website |
| title_full | Digital assistant for E-commerce website |
| title_fullStr | Digital assistant for E-commerce website |
| title_full_unstemmed | Digital assistant for E-commerce website |
| title_short | Digital assistant for E-commerce website |
| title_sort | digital assistant for e-commerce website |
| topic | T Technology (General) |
| url | http://eprints.utar.edu.my/5530/ http://eprints.utar.edu.my/5530/1/fyp_IA_2023_CJW.pdf |