Hoteliers typically resort to dynamic pricing (changing the price of rooms as per changing market conditions) twice or thrice a year. Hilton has been practising dynamic pricing since as far back as 2004. This was perhaps done manually. But with the advent of machine learning applications in the game, dynamic pricing uses predictive analytics to add variables (upcoming holidays, lifting of Covid-led lockdowns, mid-week strikes leading to office holidays etc.) in forecasting the best price.

Case in point is a predictive analytics tool developed by Starwood Hotels in 2015 which took into account a plethora of factors to arrive at the best price for a point in time. These variables ranged from weather conditions, competitive pricing data, occupancy data, booking patterns of users, and many other variables. This system can either be fully automated or help from human operators can be taken to adjust rates manually if required. When hotels get hold of the customer data as well as market data, they can get direct bookings and earn more profits than they would with third parties (such as booking portals) involved.

Among the first to adopt dynamic pricing, Hilton did it when access to technology was far less as it stands today. By using the correct revenue management software, the hotel made the shift to dynamic pricing in an absolute manner and also offered it as part of its loyalty program. The end product is flexibility, cost savings, and good revenue gains.

Matildas, a boutique hotel in Chile too is using a revenue management system with a price intelligence engine. They got better prices, more revenue, and savings on labour costs as a result of this implementation.

Hotelmize uses AI for their Room Mapping to track dynamic prices for a given room across multiple suppliers. Enter the gamechanger AI which will predict dynamic prices for a particular room, and they can now accurately know the approximate duration for which the price will remain lowest.

Flight fare forecasting: New mobile apps are helping customers find cheaper flights which they find using price forecasting applications. Bagging the best deal on flights and hotels has become that easy nowadays. Being automated, these tools scan the market and alert the users when the best deals are available. Websites such as Skyscanner and Hopper provide such services by helping customers to book cheap flights with the help of analytics. When travel agency websites add similar tools they can take a quantum leap in customer acquisition, making them book more trips, and rake in much needed revenue.

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