Enhancing Customer Satisfaction and Product Quality in E-commerce through Post-Purchase Analysis using Text Mining and Sentiment Analysis Techniques in Digital Marketing - Calvina Izumi; Soeltan Abdul Ghaffar; Wilbert Clarence Setiawan (Bright Publisher, 2025)
This study explores the application of text mining and sentiment analysis to enhance product quality and customer satisfaction within the e-commerce landscape. Using the Customer360Insights dataset, which comprises 236 records of customer interactions, demographic details, product information, and transactional data, we identified key drivers of negative feedback and returns. The descriptive statistics revealed a diverse customer base with an average age of 45.33 years and significant variability in monthly income (5,470.24 ± 1,442.80). The text mining process, including tokenization and term frequency analysis, identified frequent terms such as