In recent years, online customer reviews have become an increasingly important source of information for travelers looking to book a hotel. But are these reviews just subjective opinions, or can they be used to accurately predict a hotel’s future performance?

A recent study used customer review analysis for hotel demand forecasting. Text analysis techniques were used to identify and extract subjective information from text data.

The dataset included over 600,000 customer reviews for over 2,000 hotels in the United States. The researchers found that the sentiment reflected in guest reviews was able to accurately predict a hotel’s future performance, as measured by revenue per available room (RevPAR). In fact, it was found to be a better predictor of RevPAR than traditional indicators such as occupancy rate and average daily rate.

The study’s results suggest that customer reviews can be a valuable tool for hotel forecasting, and their analysis can be an effective way to extract valuable information from these reviews. This is good news for hotels, as it means that they can use customer feedback to identify areas for improvement and potentially increase their future revenue.

The study’s findings demonstrate how the technologies and tools implemented by Sentimantle’s solutions can be used in hotel demand forecasting. By using these solutions, hotels can better predict future demands and trends in customer preferences and adapt to them through pricing strategies and improving their service quality.

Contact us to schedule a demo and see how we can help you achieve your hotel’s goals: https://sentimantle.com/contact/

(Source: D. C. Wu, S. Zhong, R. T. Qiu, and J. Wu, “Are Customer Reviews Just Reviews? Hotel Forecasting Using Sentiment Analysis,” Tourism Economics, vol. 28,
no. 3, pp. 795–816, 2022)