Customer Satisfaction Response to Artificial Intelligence Tools Usage During Online Shopping

Artificial intelligence (AI) is a technology that enables products to be combined with new features and create innovative customer experiences . A lot of businesses have embraced various AI tools to offer customer care interactions. Research gaps arise from an unclear picture of how customers' experience with online shopping will be affected by the experience and usage of AI tools. This study aims to predict satisfied online shoppers based on their usage experience with AI tools, by leveraging data mining methods and machine learning techniques. Data was collected from India, China, and Canada in 2021 and 2022 by distributing online survey to online shoppers with exposure to AI tools. Five machine learning algorithms; decision tree, random forest, naïve bayes, gradient boosted tree and multilayer perceptron neural network techniques were applied and compared to predict satisfied shoppers using. Overall, all the models showed a prediction accuracy of more than 86.5% f-score value and random forest outperformed with 91.5% f-score value. The findings demonstrated that the online retail business can identify satisfied customers with 91.5% accuracy using machine learning. Business can derive such data-driven actionable knowledge from integrating machine learning into their operations, resulting in a more satisfied customer base and a more efficient and competitive business model.