As global attention on environmental sustainability grows, this study explores consumer perceptions of baby cloth diapers, offering insights for marketing researchers and baby care firms. Using Python-based text mining techniques, 3,216 customer reviews from a major e-commerce platform were analyzed. Methods included sentiment analysis, word frequency, topic modelling, association rule mining and clustering to extract key consumer viewpoints. Results reveal generally positive sentiments but highlight inconsistencies between star ratings and review content, challenging assumptions in online consumer behaviour research. N-gram analysis uncovered recurring patterns in both positive and negative feedback, while association rule mining and clustering identified dominant themes such as comfort, softness, dryness, leak prevention, absorbency and material quality. The lack of specific brand mentions suggests a gap in brand recognition, signalling the need for improved brand management. This study not only enhances understanding of sustainable product adoption but also demonstrates the value of mining unstructured consumer data in emerging markets. The findings support practitioners in designing effective brand and product strategies and contribute to the broader agenda of responsible consumption. Overall, this research aligns with Sustainable Development Goals (SDG) 12 by promoting sustainable consumer practices through data-driven insights.
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