What is hotel price prediction?

Hotel price prediction is the process of using machine learning algorithms to forecast the rates of hotel rooms based on various factors such as date, location, room type, demand, and historical prices.

Can ML models predict hotel prices?

OTAs and metasearch engines. Of course, OTAs like Airbnb and Booking.com as well as metasearch engines like Tripadvisor can be used as data sources for ML models to predict hotel prices. These platforms provide a wealth of data about prices, bookings, and availability for a wide range of accommodations

How can machine learning improve hotel price prediction?

Hotel price prediction is a critical aspect of the travel industry. And with the rise of machine learning, it has become more precise and accurate. The key objective behind this task is to set the best booking prices to entice customers and ensure that hotels take full advantage of their business potential.

How do you forecast a hotel?

Forecast by segment: by breaking down the forecast into deeper segments, such as GOB – where the guests are coming from; distribution channels – where they are booking from; per room type – which room type they are booking; or market segments, such as IBT, LEI, RACK or GT, CONV, CMTG, IT, and more.