Dynamic Pricing in Hotels
SmallTrain supports various data. This section describes hotel room price prediction using Small Train.
Dynamic Pricing
Predicting the price fluctuating every hour is a lot of work. Moreover, it is difficult for people to figure out the optimum value in the competition with other companies. SmallTrain considers the balance between supply and demand, compares it with the price of competitors, and then predicts the optimal price to maximize sales. If there is time series data, SmallTrainl predicts optimum price regardless of industry.
Case:
Use SmallTrain to price “hotel rooms” SmallTrain predicts prices for 6 months in advance and then predicts and optimizes the prices every day. Hotel reservations are more important for one month in advance. The room reservation status is greatly affected by the price of the hotel room reservation site. Good pricing helps the hotel maximize operating profits.
Based on data from various booking sites, SmallTrain offers you profitable prices without being too cheap.
There are many reservations and sales sites in the hotel market, and the selling price is set for each site, so the actual price paid by the customer is different from the wholesale price of the hotel.
In fact, the hotel side sometimes has only “the wholesale price of the room charge for one day” and “the total amount paid by the customer (for family)” sent from the reservation site.
Still, it does not require any additional data collection but provides “current price data” for the prediction.
