THE ADOPTION OF AI-DRIVEN CHATBOTS INTO A RECOMMENDATION FOR E-COMMERCE SYSTEMS TO TARGETED CUSTOMER IN THE SELECTION OF PRODUCT

Authors

DOI:

https://doi.org/10.62737/m1vpdq75

Keywords:

Artificial Intelligence; Chatbot; E-Commerce; Product Selection; Purchase Decision; Customer Satisfaction and Engagement; Customer Trust and Retention.

Abstract

The research looks into the Adoption of AI-Driven chatbots into a recommendation for E-Commerce systems to targeted customer in the selection of product, particularly their function in product selection and overall customer experience. The study is based on five assumptions: improved product selection accuracy, increased user happiness, influence on customer engagement and purchase decisions, enhanced user experience and retention rates, and effect on consumer trust. The findings show that AI-powered chatbots greatly improve product selection accuracy, with a regression weight of 0.693 and a beta coefficient of 0.480, representing a 48% improvement per unit of implementation. User satisfaction has also significantly improved, as evidenced by a regression weight of 0.897 and a beta coefficient of 0.840, both with high statistical significance. Chatbots have a favourable impact on consumer engagement and purchasing decisions, as indicated by substantial regression weights and beta coefficients for each variable. AI chatbots improve user experience and retention, as evidenced by high regression weights and R² values. Finally, chatbots improve customer trust, with a regression weight of 0.447 and a beta coefficient of 0.200. Overall, the study shows that AI-powered chatbots significantly increase several aspects of e-commerce, including product selection accuracy, user pleasure, engagement, retention, and trust.

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Published

2024-10-11

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How to Cite

THE ADOPTION OF AI-DRIVEN CHATBOTS INTO A RECOMMENDATION FOR E-COMMERCE SYSTEMS TO TARGETED CUSTOMER IN THE SELECTION OF PRODUCT. (2024). International Journal of Management, Economics and Commerce, 1(2), 128-137. https://doi.org/10.62737/m1vpdq75

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