Modern Revenue Management: The Core Competencies Every Property Needs
Revenue Management (RM) has been used in hotels for well over a quarter-century and has grown into a dynamic and lucrative field that focuses on optimizing the overall income-generating capability of a property. The success of RM in capturing revenue, along with the availability of customer-level data and advanced analytics and technology, has expanded the influence of RM on broader operating strategies. The continuing advancement and demonstrated achievements of RM in hotels has led to steady research and development of RM solutions and opportunities. The challenge for a property is to find and apply the RM theories, tools, and techniques that cultivate long-term profitability across the organization.
For a casino hotel, this can be an especially complex assignment, as multiple factors – gaming, rooms, food & beverage, retail and entertainment – must cooperate to optimize the flow of profit through the property. An effective modern Revenue Management program should provide an understanding of customer buying behavior, which should then be factored into optimization algorithms as a way to account for individualized customer reinvestment rates. The resulting rate recommendations will be personalized and reliable and well as responsive to changing economic and operating environments.
The core competencies every casino property needs to best use Revenue Management in the modern era include next generation, cutting-edge elements mixed with updated classic factors. As Revenue Management has evolved and become more sophisticated, RM core competencies have become operational as well as strategic. Machine Learning and Artificial Intelligence are providing new capabilities in data analysis and RM modeling, which allows for new approaches to segmentation, pricing, and distribution. An enterprise-wide RM culture connects all aspects of RM and provides a common focus on the goal of optimizing the long-term value of customers.
The most dedicated and effective applications of hotel revenue management have expanded beyond data analytics and become the basis for broader decision-making. In fact, adopting an enterprise-wide culture of RM has proven to be a highly successful way to provide a common objective for all areas of a property. As a modern core competency, promoting a ‘revenue management culture’ helps direct revenue centers away from maximizing local, or department-level revenue and toward the goal of optimizing global profits.
It is particularly important for the hotel’s marketing, sales, and revenue management teams to work together. Otherwise, the property will miss valuable opportunities; and, quite possibly, waste money because the departments are working at cross-purposes. If, for example, the hotel is lacking demand in the group segment, the sales team can provide insight into how to attract this segment. If ancillary numbers are low, the marketing team can create offers and incentives that drive on-property spending. Knocking down departmental walls helps ensure that the hotel’s decisions are guided by a common objective, and preference is being given to the right segments at the right time.
Additionally, a revenue management mindset fosters flexibility and adaptability, as RM naturally changes recommendations to take advantage of current market and operating conditions. Inputs to a hotel—such as customers, personnel, market trends, and economic conditions, —are relatively dynamic, and a RM culture helps a hotel stay flexible and competitive.
Focus on Total Customer Value
For many years, hotel Revenue Management was considered a tool that was useful only in situations of excess demand to capture the most RevPAR available. However, as RM has expanded to a wider demand management role, it now encompasses much more than room revenue and is concerned with all profit centers and customer-level information, including acquisition costs and shopping behaviors. Over time, the pattern of a customer’s spend across all areas of a property indicates the overall value of that customer.
For casino hotels, the profitability ‘formula’ must always include equalizing gaming and non-gaming customers. Typically, the profits from gaming guests are higher than those from non-gaming guests, because the margins on gaming are better. Why? Because the expenses involved in keeping the slot machines operational are far less than those required to operate a salon, a spa, or food and beverage outlets.
Also, keep in mind that all guests are not the same. Although the ADR can represent the buying power of a customer, it also can be misleading. For example, a couple who has saved for months to take a dream vacation to Las Vegas may spend a great deal of money on a suite for several nights, yet spend almost nothing on ancillary services. Moreover, they may not visit the property again. On the other hand, a businesswoman may visit the hotel for only two nights, but spend money in the bar, the restaurant, the spa, and the gift shop. And, she may stay at the hotel whenever she is in town.
The optimal way to maximize revenue — regardless of guest behavior — is to follow total customer valuation as closely as possible. Although most casino hotels do a good job of assessing the long-term value of guests through player and loyalty tracking, progressive properties are forecasting total guest value; and, as a result, can offer availability for their most valuable customers. Moreover, guests are being rewarded based on total spend across the property, which promotes loyalty and ends the costly practice of excessive discounting.
Implement Machine Learning and Embrace Artificial Intelligence
Innovative technology provides the platform for effectively applying modern RM. Machine Learning (ML)—the ability for a model to automatically adjust and improve its performance based on patterns it recognizes in large amounts of data—has emerged as a popular technique of modern RM. RM technology has always been an integral part of effectively applying RM, and next generation systems are adept at supporting extensive data collection and using ML to mine through the volume of information and refine algorithms to get the best results possible.
Artificial Intelligence (AI) builds on the predictive analytics of ML and moves into prescriptive analytics, which provide solutions and recommendations. AI is a proactive approach to data modeling that is able to critically assess and even generalize the feedback generated by ML. Modern Revenue Management systems are poised to take full advantage of AI by automatically collecting customer-level data, performing ML-based optimization algorithms, and distributing inventory through the appropriate channels.
Revitalize Segmentation Strategy
A classic core competency of a hotel Revenue Management program is the ability to segment demand based on customer characteristics such as price sensitivity, booking behavior, purpose of travel, and intended use of the property. An effective segmentation strategy accounts for the fact that different guests have different preferences and willingness-to-pay profiles. Applying ML and AI to segmentation allows a casino hotel to identify and serve a high-value customer mix for each segment and across all segments. The ability for a property to consistently respond to customer differences with tailored products and prices helps it capture and even influence all types of hotel demand.
Modern RM utilizes a narrow segmentation strategy where customer segments are tightly defined. This results in a property identifying and serving many customized micro-segments, which are very small market segments differentiated by distinct customer attributes. Using micro-segments for RM purposes allows a property to practice skillful pricing and targeted marketing to ensure that the most valuable customers are always accommodated. Establishing functional micro-segments requires robust customer data and advanced analytics capabilities, both of which are available and accessible to hotel operators. However, enough data must be available to accurately forecast, price, and manage each micro-segment.
Next generation Revenue Management optimization models have moved beyond allocating rooms to static product categories and price buckets. Complex dynamic pricing models have proven to be more effective at controlling how and when rooms are sold. These advanced models use Machine Learning to analyze large amounts of customer-level data and use price optimization models to provide operators with reliable, data-driven pricing recommendations. To best manage the total value of a guest, properties need to ensure that rates reflect spend across the whole property and account not only for broader market trends but also for expected demand for rooms, gaming, entertainment, F&B, spa, and retail in pricing decisions. Artificial Intelligence-based systems automate this process and determine what prices should be offered through which channels at what time, while keeping an eye on, but not always reacting to, competitor prices.
Use Value-driven Distribution
Distribution of hotel rooms for sale has advanced and expanded due to the proliferation of third-party sellers and resourceful customers with value-driven behaviors. A modern distribution strategy calls for optimizing a hotel’s channel mix to ensure that the right type of supply is being offered to the right customer in the most profitable way. Simply minimizing the cost of distribution is not necessarily a revenue-maximizing solution, as different customer segments are reached in different ways. A distribution strategy should account for the value-creating “billboard-effect ” which is the phenomenon that having a presence on an OTA drives bookings to a property’s own site, even if the OTA is not one of the most profitable distribution channels. .
The rapid and steady shifts in hotel distribution have provided opportunities for development, and a competitive distribution system must be flexible and adapt to market and operating changes. Because OTAs are currently able to charge high commission rates, hotels are developing value propositions that encourage customers to book directly; casino hotels are especially adept at using player loyalty programs to create value for customers booking on the property’s own site. Mobile technology and social media distribution channels provide further opportunities for a property to bypass OTAs and directly connect to customers at the booking stage.
Revenue Management has proven to be a profitable practice that connects data, theories, and methods from multiple areas and provides a framework for a property-wide operating strategy. Over the years, the field of RM has expanded and evolved and is now in a position where cutting-edge technology and big data capabilities are merging with direct marketing. Customer segmentation, pricing, and distribution are some of the classic core competencies of RM that have been augmented and automated by the modern RM core competencies of using Machine Learning and Artificial Intelligence. As a casino hotel continues to focus on optimizing the lifetime value of each customer and using the progressive tools available, its RM program will strengthen into a robust, market intelligence tool that links history to future expectations and customer and market trends to lucrative Revenue Management solutions.
This article was previously posted in the April 2018 edition of Indian Gaming Magazine.