A fully-automated solution that optimizes hotel wholesalers’ profits from existing sales. This unique, highly efficient solution gives hotel resellers the strategic ability to enhance yield from existing sales by improving their industry-standard purchasing processes while delivering exceptional added value and customer service.
The Rebooking Solution enables hotel distributors, bed banks, wholesalers, and travel agents to increase their profitability by over 35% by using innovative technology.
Increase your profitability by over 35%
The big difference today compared to several years ago is the increasingly volatile nature of price movements in the travel industry. On average the price of that booking will now change almost 18 times until it’s time to check-in. This is when the rebooking solution comes in, with its machine learning and Big Data technology powered by AI, to compare fluctuating hotel rates and predict when the price will reach its absolute bottom.
In just a few simple words this is how the ingenious rebooking solution enables travel companies to uncover hidden revenue opportunities and uplift hotel booking profits and margins.
using Big Data
Big data can provide predictive analysis of demand based on a range of factors such as historical performance, seasonal attractions and events, weather, public and school holidays. It can also identify new trends in the types of travel bookings made such as solo travel, leisure, and digital nomads.
Big data’s core strength lies is in the ability to adjust prices quickly and competitively in response to a predicted change in travel demand. Rebooking solutions optimize the gain of hotel resellers by raising their profit margins using price prediction technology that utilizes artificial intelligence (AI) and big data solutions to uncover the best available rate from the moment 0 of the booking until the check-in is done and it rebooks the travel service at its lowest rate.
The rebooking solution is compatible with all booking systems and runs seamlessly in the background, so it doesn’t require any change in workflow.
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