Keywords
Personalized Online Shopping
Impulse Buying Behavior
Seamless Interaction
Voice Commerce
How to Cite
Abstract
Growth of technology and innovation is inevitable. Using natural language processing along with machine learning, this technology allows voice assistants to detect user preferences. Voice assistants would suggest products that are suited to the user, smoothen the buying process, and show a user interface that is in tune with the user's way of shopping behavior. The innovation copes with the challenges of limited visual comparison by adding context-aware suggestions that improve the engagement of users and enhance their confidence in the purchase decisions made through voice interactions. Our study is multifaceted in its blend of survey and interview approaches, investigating the psychology and behavior of consumer interactions. The study emphasizes impulsive purchase behavior influenced by this personalized technology. The SEM methodology was used for data analysis and hypothesis testing in connection with the voice assistant's features and online consumer decision-making process. This research offers several useful insights regarding the still-evolving voice commerce and its implications for businesses to enhance user engagement and satisfaction with personalized online shopping. The study presents both an innovative framework for voice-assisted e-commerce and discusses the rich dynamics between technological development and consumer behavior in the digital marketplace.
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