Authors : Ong Tzi Min; Lim Tong Ming

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/3xschtbk

Scribd : https://tinyurl.com/bdh9any3

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY2413

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : In today's fast-paced consumer electronics industry, staying ahead of the competition and satisfying customers are top priorities. This research investigates the use of AI-powered tools, particularly conversational AI and chatbots, to improve customer interaction and boost sales in electronic retail. As digital platforms become more dominant over traditional sales channels, these AI tools offer significant benefits by delivering personalized, efficient, and timely customer service. The analysis examines various AI technologies, including Large Language Models (LLMs) and retrieval- augmented generation, which enhance consumer interaction. The study also explores the practical implications and challenges of implementing these technologies, with a focus on how they can streamline operations, improve customer experiences, and drive sales. Different models like DialoGPT, Flan-T5, and Mistral 7B are evaluated for their effectiveness in real- time consumer interactions, highlighting the importance of continuous adaptation and learning within AI systems to meet consumer demands and keep up with technological advancements.

Keywords : Chatbot; LLM; Mistral-7B; Flan-T5; DialoGPT; Lang Chain; Transformers.

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