TRANSFORMING MYSTERY SHOPPING WITH ARTIFICIAL INTELLIGENCE: A PARADIGM SHIFT IN REAL-TIME CUSTOMER EXPERIENCE EVALUATION AND STRATEGIC INSIGHTS

Abstract

This research focuses on how AI can revolutionize the concept of mystery shopping, an important method for gauging customer satisfaction in recent times. Previous approaches to mystery shopping had their problems, including bias, high cost, and long feedback time. Through incorporating the use of AI automation the following challenges can be overcome that is improved accuracy in data analysis, reduced costs, and feedback which is real time. Automated tools such as sentiment analysis, natural language processing, and machine learning algorithms produce a more fair and evidence-based assessment of the customers’ engagement. Regarding resource usage, AI is highly efficient in its usage of resources since through automation, companies receive constant support and feedback on improving the quality of customer service, which occurs at fixed intervals. This paper discusses and analyses the current uses of artificial intelligence in mystery shopping as well as comparing the advantages of the technology and envisioning how it may further change the evaluation of customer experience in the future.