A Study on User's Satisfaction Towards AI Powered Product Recommendation with Special Refference to Coimbatore City

The advent of Artificial Intelligence (AI) has revolutionized the e-commerce landscape with personalized productrecommendations. This study investigates user satisfaction towards AI-powered product recommendations, examiningthe impact of recommendation accuracy, interface usability, and trust on overall satisfaction. A survey of 70 onlineshoppers revealed significant correlations between recommendation relevance, user experience, and satisfaction.Results show that AI-powered recommendations increase user engagement, purchase intentions, and loyalty.However, concerns regarding data privacy and algorithm transparency emerge as critical factors influencing user trust.This research contributes to the understanding of AI-driven recommendation systems' effectiveness and highlightsareas for improvement to enhance user satisfaction

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-26
DOI
https://doi.org/10.5281/zenodo.14220303
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

A Study on User's Satisfaction Towards AI Powered Product Recommendation with Special Refference to Coimbatore City

Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

A Study on User's Satisfaction Towards AI Powered Product Recommendation with Special Refference to Coimbatore City

article en

Abstract

The advent of Artificial Intelligence (AI) has revolutionized the e-commerce landscape with personalized productrecommendations. This study investigates user satisfaction towards AI-powered product recommendations, examiningthe impact of recommendation accuracy, interface usability, and trust on overall satisfaction. A survey of 70 onlineshoppers revealed significant correlations between recommendation relevance, user experience, and satisfaction.Results show that AI-powered recommendations increase user engagement, purchase intentions, and loyalty.However, concerns regarding data privacy and algorithm transparency emerge as critical factors influencing user trust.This research contributes to the understanding of AI-driven recommendation systems' effectiveness and highlightsareas for improvement to enhance user satisfaction

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 65%
AI in Service Interactions
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