In today’s business world, social media has become more effective than traditional print media for interacting with customers and understanding their needs. This analysis is initiated to provide insights and recommendations to improve customer satisfaction, enhance business strategies, and strengthen the accommodation and hospitality industry in India. The Natural Language Processing (NLP) models like BERT, VADER, and XLNet, play a pivotal role in analyzing reviews and feedback, thereby providing opportunities to enhance business standards. In our study, we focused on identifying areas for improvement in the maintenance and performance of OYO hotels in Bengaluru by analyzing reviews and feedback from stakeholders. We also conducted a comparative study on the performance of the BERT, VADER, and XLNet models. To ensure accuracy, we combined the results from these models using an ensemble method and the accuracy rates we achieved before and after the ensemble were: BERT improved from 89.33 to 90.21%, VADER from 92.0 to 94.51%, and XLNet from 95.34 to 96.24%. The insights gained by using these advanced techniques are helpful to tailor marketing strategies, market positioning, and helping hotels to identify their unique selling propositions (USPs) and areas where they can excel and also scope for improvement.