Unveiling Key Drivers of Customer Satisfaction in Women’s Clothing: A Topic Modeling Analysis of Online Reviews

This study explores customer reviews of women’s clothing to find out the factors influencing customer satisfaction using STM. The model provides a deep-level insight which can be used at the industry level. By analyzing textual data, we identified key themes such as fit, comfort, material quality, and design preferences, which significantly influence consumer perceptions and buying decisions. The STM model was trained with five topics, and insights were drawn by analyzing the most probable words, FREX terms, and lift scores for each topic. Visualizations, including coherence scores and topic prevalence plots, were employed to validate the model’s reliability. The findings reveal that customers prioritize aspects like fabric quality, size accuracy, and style, while also highlighting concerns about product durability and fit inconsistencies. Regression analysis further showcases the influence of customer ratings and departmental categories on topic occurrence. This comprehensive analysis offers actionable insights for retailers and manufacturers to improve product distribution and customer satisfaction, thereby enhancing competitiveness in the women’s clothing industry.