<![CDATA[The COVID-19 pandemic has significantly impacted the retail industry, particularly shopping malls, which have experienced a 30% to 40% decline in customer footfall in the first quarter of 2021 compared to previous years. Despite the growing body of research on retail recovery, there remains a gap in understanding specific customer sentiments and experiences within mall environments during this period. This study aims to address this gap by analyzing customer feedback extracted from Google reviews to identify key attributes influencing the shopping experience. The research employs text-mining techniques to convert unstructured data into structured formats, eliminating irrelevant words and concepts. Following data cleaning, the Naïve Bayes Classifier method is utilized to analyze the sentiments, achieving an accuracy of around 92.86%. The findings will be visualized through word clouds and bar charts to highlight the top ten positive and negative sentiments expressed by customers. Ultimately, this research contributes to enhancing the customer experience at shopping malls by collaborating with relevant stakeholders to create a comprehensive Customer Journey Map based on the analyzed data. This map will serve as a strategic tool for mall management to implement targeted improvements and foster a more engaging shopping environment.]]>
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