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Foodservice firms have been among the most affected business units during the COVID-19 pandemic. The slew of lockdowns and resulting apprehensions of contracting virus infections have largely deterred customers from patronizing various food outlets. However, with internet assistance consumers have increasingly found perceived refuge from unsafe dining experiences. As a result, the paper makes attempt to identify the determinants of customers' dining experience in restaurants. A total of 1,545 customer reviews from 97 foodservice outlets of 14 Indian cities were collected. R programming was used to perform qualitative analysis on the reviews to identify the features. Bigram analysis was applied to calculate the repeated phrases. Based on the repeated phrases, researchers measured the factors that contribute toward the customers' dining experience. The findings suggest that food quality and taste, food variety, staff behavior, restaurant ambience, along with social distance and safety norms mainly determine guest satisfaction. The findings also reveal that hotels need to apply recovery strategies such as training staff to adapt to the new-normal strategies and provide a safe environment to improve restaurant businesses. This study uses novel dataset and the findings essentially contribute to the food service literature. Further study can be done using big data in varied settings. [ABSTRACT FROM AUTHOR]