This research explores the determinants and implications of brand attachment in the fast-growing online meal-kit industry. The objectives were to explore the components constituting the system and food quality, establish their impact on brand attachment, and examine the subsequent impact on consumer behavioral intentions. Utilizing big data analytics, the study analyzed real-time app content sourced from consumer reviews using a text mining technique and employed structural model analysis to validate a proposed model with five emerging factors from the consumer review data. The findings suggest that system quality parameters—perceived ease of use and perceived usefulness—significantly influenced food quality. Enhanced food quality cultivated brand love yet reduced brand hate. Notably, brand love and hate exhibited opposing correlations with negative electronic word-of-mouth and continuous usage intention. The outcomes secure crucial insights for ongoing engagement with online meal-kit services, significantly contributing to academic research and industry practice.