Do hotel revenue managers need to panic about one day being replaced by robots?

An AI humanoid called Sophia has become the first robot citizen with feelings, preferences, and the capability to learn much faster than humans. Besides that, it turns out AI can even write pretty good songs. Researchers at Sony released the AI-generated song, "Daddy's Car," a catchy, sunny tune reminiscent of The Beatles. Last year, Facebook abandoned an experiment and shut down two AI robots after they started talking to each other in their own language, which remained mysterious to the scientists who were supposedly looking after them. It looks like robots are one step closer to taking over the world.

But what about our world? The wonderful and colorful revenue management world? How does AI influence our daily jobs?

First coined in 1956 by John McCarthy, AI involves "machines that can perform tasks characteristic of human intelligence," including planning, understanding language, recognizing objects and sounds, learning, and problem solving. Today, with the collection of customer data, coupled with continued improvements in computer technology, AI can perform a wide range of routine tasks, from basic customer service to personalized job duties, more advanced decision-making, even sales processes and direct messaging.

Professionals from all different fields use AI for predictive analysis and interpretation. AI is one of the biggest trends in tourism and related fields, and hoteliers are also using big data and AI to innovate their pricing strategies. AI combined with data analytics will enable the automation of many daily tasks. Therefore, when human participation and manual work becomes unnecessary, we should find a good balance between the human resource and machine, and reasonably allocate our time on what we are good at.

Among the most repetitive tasks, AI technology can take on the burden of large amounts of demand and pricing analysis. Hoteliers look forward to and appreciate this change when they experience explosive data growth. Today, the production of various daily reports takes more and more time with the increase of data elements and analysis dimensions. The amount of time spent on this data processing and reporting is bound to affect the scheduling of more important analyses and decisions, so it is far more efficient to leave these repetitive tasks to AI.

In addition, the data analysis methods of AI nowadays are getting more accurate, and more data analysis normally leads to more insights. Allowing AI to complete more accurate data analysis leads to more rational decision-making and can be another great benefit to revenue managers, leaving them with more time to monitor the automated decisions based on the analysis, focus on the implementation and make proper adjustment to the decisions.

AI can also be applied to different research tasks, such as generating specific market segments, which can reveal the implicit correlation between customer information and preferences. Traditional hotel revenue management systems are based on a pre-set market segmentation model for future demand forecasting and management. With AI, more advanced revenue management systems would automatically assign attributes to more detailed rate code levels to generate its own forecast group, based on both attributes and historical booking patterns. For example, two market segments may have the same attributes, and may be grouped together. But meanwhile the system may place them in two different forecast groups after analyzing their booking patterns and finding they differ greatly regarding the timing of when the business books. The advantage of doing so is to divide the forecast group as much as possible according to the actual business attribute and behavior pattern, rather than only relying on the existing market segmentation system, which may be wrong, resulting in inaccurate forecast.

Also, with AI and a machine-learning algorithm, the revenue system can evaluate the nearest competing hotel's demand level, competitor pricing, destination special events, room type, and so on. Demand forecasts provide critical information for pricing decisions for each market segment or room class and can help revenue managers to select appropriate distribution strategies, as well as explore what customers want and describe their price sensitivity.

An intelligent, data-driven revenue management system can greatly improve pricing efficiency. For example, in some international hotel groups, the machine-learning-based revenue management system combines different strategies and data sources to set a best available rate for each room class on each date. The algorithms behind this dynamic pricing engine take into account both customer profiles, room types and prices, as well as external data, such as competitor prices, reputation score data, and even booking patterns captured on other websites.

In addition to pricing, another important aspect of revenue management is inventory control. The key point of revenue management is optimizing revenue and profit through proper pricing and space controlling of hotel rooms, meeting space, restaurants and other entertainment areas. Revenue managers seek to capture the opportunity to increase prices and maximize revenue on high-demand dates while maximizing occupancy on low-demand days. In this case, the AI-based, advanced revenue system can automatically make decisions and select the revenue strategies applicable to different market segments. The system needs to be able to select the best space control strategy to achieve the best deal, the commonly used inventory control strategy including the minimum or maximum length of stay, closed to arrival, block or allotment set up, the last room availability, and so on.

Last but not least, a hotel's success is often due to the personalized service and unique experience it offers guests. With the help from AI, combined with human experience, the tasks of identifying the hotel demand model, looking for revenue growth opportunities, and using digital marketing to boost market demand can be done in a much more accurate and effective way.

So, a trusting AI system is the best thing to have at the moment, but hotel revenue managers do not need to panic about one day being replaced by robots. No matter how advanced the AI revenue system gets, it will always require a human touch and interaction. Therefore, the future trend is that the hotel will inevitably use AI data analysis to make better optimization decisions to grow revenue and enhance profit performance.

Revenue Management