ShopTips: Design and Development of an AI-Based Web Application for Automating E-Commerce Product Marketing Content

Yoga Handoko Agustin, Alwan Nugraha Putra

Abstract


The rapid growth of e-commerce has prompted sellers to produce compelling product descriptions quickly and efficiently. However, many sellers lack the copywriting skills needed to craft persuasive marketing content from raw product specifications. This research aims to design and implement ShopTips, an AI-powered web application that transforms product data into ready-to-use marketing content. The system was developed using a web-based architecture consisting of an HTML/CSS/JavaScript frontend, a Node.js with Express.js backend, MongoDB as the database, and an external AI API for natural language generation. The development methodology followed the Waterfall model, encompassing requirement analysis, system design, coding, testing, and evaluation phases. ShopTips enables users to input product details such as name, category, description, specification, target market, and sales platform. The system then generates persuasive product descriptions, Unique Selling Points (USPs), SEO keywords, call-to-action phrases, social media captions, and a multi-dimensional content quality score encompassing clarity, persuasion, SEO, and emotional dimensions. In addition, the application provides structured feedback to help users refine and improve their content iteratively, making it a practical tool for both novice and experienced sellers. The system is also designed with a simple and user-friendly interface to ensure ease of use and accessibility for micro, small, and medium enterprises (MSMEs). Functional testing using black-box methods showed that all eight primary endpoints operated as intended without critical errors. User acceptance testing with 30 respondents yielded a satisfaction score of 85.6%, indicating high acceptability and usability. The findings demonstrate that the application significantly reduces the time required to produce marketing content while improving overall content quality. Therefore, ShopTips can serve as an effective solution for sellers who lack advanced writing skills and need efficient content generation tools. Future research may explore user authentication, export features, direct marketplace integration, and competitor analysis functionality to further enhance system capabilities and scalability.

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DOI: https://doi.org/10.37058/jaisi.v4i1.18221

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International Journal of Applied Information Systems and Informatics (JAISI)
Department of Information Systems, Faculty of Engineering, Siliwangi University Tasikmalaya
email: jaisi@unsil.ac.id

Jalan Siliwangi No. 24 Kelurahan Kahuripan Kecamatan Tawang Kota Tasikmalaya 46115

This work is licenced under a Creative Commons Attribution 4.0 International Licence