Hotel bookings around the world have changed much faster than what the industry had anticipated. With the proliferation of smartphones and fast internet, most travellers are now searching and booking hotel rooms around the clock via their mobiles. Hotels around the globe see almost more than 70%-90% of their rooms booked online on OTAs like Booking.com & Expedia. As per the Expedia Millennial Survey, 62% of the Indian millennial prefer to book their tickets through an online travel agency, and 19% of them prefer to book through the airline & hotel websites directly. Moreover, the average booking window (the period between booking and check-in) is reducing drastically, in many cases to last 48 hours and in many cases to last 24 hours. This change has led to a paradigm shift for revenue management and pricing for hotels.
Hotel rooms are a perishable inventory (like airline seats and movie tickets), which need to be priced appropriately because if they go unsold, they will never be recovered back. Hence, the need to use AI for pricing hotel rooms has become even more relevant in today’s fast-changing and impatient world. Revenue managers should no longer be forced to collect reports from various disparate systems and crunch daily numbers in an Excel spreadsheet to determine the right rates. By using automation and AI, hotels can now start maximizing their occupancy, increasing their ADRs (Average Daily Rates), and reducing their overheads.
Historically, hotels would base their pricing decisions only based on past data and analysis; however, this is only valid if we assume the industry and competition remain stagnant. In most leisure& business destinations, the market trends of occupancy and rates are significantly different every year, and hence past data cannot be used as a sole predictor of rates for the current season. Markets have either witnessed a hyper-growth in demand or slump in the economy. Moreover, several external factors like geopolitics, climate change, and changing competition make the demand for hotel rooms very unpredictable. These factors often make the task of pricing hotel rooms very complex, and hence there is a need to rethink and redesign the current paradigm. The need to introduce innovation around machine learning and real-time decision making can help hotels forecast demand more accurately, and take optimal real-time pricing decisions, and in turn, drive more revenue and profitability.
As per the market reports by 2021, the global smart hospitality market will increase to US$ 18.1 billion at a CAGR of 25.8 per cent. This will be driven by hotel automation platforms, which can generate a global market of US$ 4.3 billion by 2021, at 6.5 per cent CAGR. Prices now need to be changed several times a day, or even several times an hour by an automated system to maximize the occupancy & revenues, and this cannot be done with any manually operated system.
Prior to the inception of this automation, hotel rates were often decided by hotel & revenue managers and manually entered into the extranets of Online Travel Agencies or Channel Managers, which was time-bound and often a slow and inefficient process. Rates could only be changed a few times a day, depending on the time and availability of revenue managers and only for a few days, depending on constraints of linear human understanding. This would often leave money on the table because the last room could have probably been sold at an even higher price, or the excess capacity could have probably been increased if the prices were lowered systematically during the last hours of the day.
There is clearly a need for advanced automated revenue management & dynamic pricing systems in the hotel industry. The marketing & revenue management teams of hotels who are typically responsible for managing online marketing can now be made more productive, or in some cases be completely replaced by pricing robots thereby increasing efficiency for the hotels.
Hotels have recently witnessed a lot of automation and innovation around guest experience and augmented reality. It is time that concepts like artificial intelligence and machine learning also enter the field of marketing & pricing, and not just directly related to enhancing the superior guest experience. There are few hotels utilizing AI and ML in their rooms, many of them began using Facebook Messenger way back in 2014 to answer guests’ queries, let them make reservations and check availability, uses its customer relations staff to help guests on the platform. The industry has typically been slow in embracing new trends in modern technology and automation and it is time to redesign a brighter future.
Mr Siddharth Goenka
CEO and Co-Founder, Aiosell
Begin typing your search above and press return to search. Press Esc to cancel.
[contact-form-7 id="7374" title="subscribe"]