It is time that concepts like Artificial Intelligence and machine learning also enter the field of marketing and pricing, and not just directly relating to enhancing superior guest experience, says Siddharth Goenka, founder, Aiosell Technologies
Hotel bookings around the world have changed much faster than what the industry had anticipated. Players in the sector have recently witnessed a lot of automation and innovation around guest experience and augmented reality.
Hotels around the globe see almost more than 70 per cent-90 per cent of their rooms booked online on OTAs. As per the Expedia Millennial Survey, 62 per cent of the Indian millennials prefer to book their tickets through an online travel agency, and 19 per cent of them prefer to book through the airline and hotel websites directly. This change has led to a paradigm shift for revenue management and pricing for hotels.
Technology adoption is needed in the hospitality industry for several reasons. The ubiquitous availability of internet and smartphones have made millennial and modern guests more discerning and wanting more experiential and personalised services. Moreover, increasing competition makes it even more important for hotels to differentiate themselves, and technology is turning out to be a big USP 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. The ease of internet on smartphones has made two primary changes in the hotel booking patterns: Customers are increasingly buying hotel rooms online, which reduces the role of traditional travel agents and offline channels. 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.
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 maximising 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 and 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 economy.
Moreover, several external factors like geo-politics, 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 maximise the occupancy and revenues, and this cannot be done with any manually operated system.
Drivers of change
In terms of sales and marketing, AI and automation have been the biggest drivers of change when it comes to dynamic pricing and automated revenue management. Most hotels are seeing a major percentage of their bookings come from smartphone and internet users, and the usage of integrated pricing and distribution systems that use AI and ML to optimise rates has become even more important to maximise revenues and minimise efforts.
Prior to the inception of this automation, hotel rates were often decided by hotel and 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 and dynamic pricing systems in the hotel industry. The marketing and 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.
There are few hotels utilising 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, and use 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. The existing legacy systems and infrastructure, fixed and inflexible mindsets of hotel owners and staff, along with inertia of embracing the unknown are some of the main challenges that are slowing down the adoption of technology across the industry. However, things are changing really drastically and with the availability of efficient, cost-effective systems that are easy to transition to, it is not too long before hospitality industry goes through a technology revolution.