The hotel sector has never been a stranger to the winds of change. What was once considered leading-edge customer service practices, like offering free internet to guests or express checkout options, are now basic expectations that travelers view as standard services. Just as the hotel industry has evolved over the years, so have the approaches that hotels have taken to attract the right guests at the right prices.
Revenue management has been used successfully in the hospitality industry for decades. However, early revenue management systems focused primarily on demand management. They did not commonly focus on optimizing price as a lever, but rather as opening and closing the rate structures that a hotel already had. Over time, and with the entrance of online travel agents (OTAs), revenue management systems evolved to meet the changing needs of the hotel industry and its operating environment – eventually becoming tasked with optimizing prices for guest rooms.
The practice of revenue management, and the systems used to make accurate pricing decisions, have become even more precise and sophisticated in recent years. Most recently, these systems have begun incorporating data on competitor pricing activity and the pricing of services outside of guest rooms, like function spaces. Undoubtedly, the biggest change in revenue management today is the influx of large volumes of guest data and its impacts on future pricing decisions and hotel promotion.
Data, Data Everywhere
Good revenue management decision making starts with good data. The data sources that support revenue management commonly include: stay history, inventory history, future reservations, future inventory and future rate information. While this data has been historically recognised as fundamental to practicing revenue management, it has also become more widely understood in recent years that the more data gathered – and the longer it is kept for – becomes even more valuable. By gathering future reservations data, hoteliers can build and asses the booking profiles of its guests and examine if these profiles are seasonal or experience any changes over time.
There is no argument that good data is critical to today’s successful hotel operations. But how did the amount and types of data that hoteliers use in the revenue management process become so important? The short answer is that today’s big data exists largely in part of the changing ways that hotels are interacting with guests. This has been driven primarily by changes in hotel technology over the last 30 years, including:
- In the 1980s, the hotel industry operated its bookings using internal systems. The relationship with the guest was one-to-one, or one-to-one with the agent. Data was retained in hotel systems such as the property management system, back office, point of sale and telephone/entertainment systems.
- The introduction of global distribution systems (GDS) to the hotel sector gave external parties a real insight into a hotel’s availability for the first time. Revenue management grew out of a need to manage bookings in this changing environment – although its early focus was on capacity and demand management. Revenue management in its early days helped hoteliers decide how many rooms to make available to a GDS or central reservation system.
- The growth in internet popularity led to more people researching and booking travel online, providing an opportunity for OTAs to grow their businesses. When OTAs began operating, hoteliers were tasked with providing them a price along and an inventory of rooms. This led to the core functions of the revenue management system changing to account for a need to optimize price. As consumers were able to compare rates between hotels, and price transparency became a prevailing issue, pricing decisions needed to be influenced with competitor price information.
- In recent times, hotels have witnessed a huge influx of data delivered by online ratings and reviews, social media interactions and mobile (location) data. Revenue management evolving even more to incorporate these new data sets and to support a hotel in attracting the right guest, at the right time for the right price.
As the way the hotel industry and revenue management has changed over the years, so has the relationship between a hotel and its guests. Whereas some thirty years ago the guest relationship with a hotel was direct, personal and on a one-to-one basis, that interaction could now be characterized as less personal and more of a digital relationship. Given this scenario, how can hotels provide unparalleled hospitality to guests and drive loyalty when the hotel’s first interactions with potential guests are often virtual? The answer: big data and analytics.
Revenue Management: Big Data and Big Analytics
More and more hoteliers are beginning to realize that big data can be valuable in supporting revenue managers and revenue management systems. Big data provides value by helping inform revenue managers during the establishment of pricing strategies, as well as driving automated solutions and analytics.
In the age of big data, advanced analytics are critical. Any revenue manager working without the support of an analytical revenue management solution will find themselves overwhelmed by the sheer volume of information and complexity of the data to make sense of. Forward-looking predictive analytics, embedded in today’s advanced revenue management systems, help hoteliers uncover emerging trends and identify opportunities. But how do these analytics support a hotel in taking advantage of big data today?
Let’s start with text analytics. Text analytics can help hoteliers understand what customers are saying in their reviews, what they’re talking about and how they feel about it. To take advantage of text analytics, competitor price information and account for customer elasticity, hoteliers can use advance time series forecasts in combination with other methodologies – including regression and revenue management specific algorithms that optimize fares and rates.
With web analytics, hoteliers are able to use web data to track the paths of individual customers: who they are, where they visited on a hotels website, what they did on the site and ultimately why they were there. Web data and web analytics can help a hotel streamline website processes that increase inquiry to booking conversions and promote the right offer at the right time.
Social media and reputation information are also valuable in informing revenue managers on their customer perceptions when they are making rate strategy decisions. Social media activity provides hoteliers with the ability to find out what customers are saying about their business, whether it relates to the service, the brand or the perceived value for money at the hotel. Understanding the perceived value of a hotel is a critical factor in the hotel’s marketing and pricing strategy, since value perception directly impacts the ability to capture demand.
Analytics to Personalize the Guest Experience
Hotel managers may struggle to balance meaningful guest experiences aligned with the brand promise with meeting their profit obligations to shareholders, stakeholders and owners. If a hotel puts too much emphasis on the brand promise (perhaps providing too many expensive guest amenities) they may throw off their profitability. Too much focus on shareholder obligations (such as cutting front desk staff to save on labor costs and adversely creating long check-in waits) negatively impacts the brand experience. Analytics can help identify the right balance between these critical aspects of hospitality enterprise.
Savvy hoteliers are realizing that the key to personalizing a guest stay, without creating unprofitable situations, is infusing analytics throughout the guest journey. And to do this, hotels must capture relevant customer data to form a better understanding of their guests.
Today’s digital environment has created more competition for the hotel consumer than ever before. This competition is not just about competing with one another and the big global brands anymore; hotels are now competing with third party distributors and disruptors from the sharing economy, like Airbnb. Hotels do, however, have one distinct advantage over all of this competition: engage with guests, collect data about them and provide an experience that third party distribution partners cannot. This is primarily why today’s hotel companies are talking at length about personalization and struggling to win back consumers through increased digital engagement.
To create a holistic view of a hotel’s guests, and to offer opportunities for personalizing a guest’s stay, predictive modeling must also be applied to the consumer demographic and behavioral data that is gathered from all of their hotel interactions. This approach allows hotels to improve their segmentation and group customers together that behave similarly so they can better target marketing messaging to them.
With predictive modeling, a hotel can also better calculate a guest’s likely lifetime value and understand how to nurture and grow the value of their most valuable guests. It can help predict the next best offer for each guest to maximize their likelihood of responding, or even encourage them to purchase additional products or services. Without today’s predictive modeling, marketing efforts are based on generic business rules that face limitations in influencing behavior. The digital environment provides opportunities to gather more diverse information about guests, and interact with them in new and creative ways. To be successful, it is important that hotels make the discipline of behavioral modeling the core of their marketing initiatives. Working together to maximize opportunities and revenues.
How can a hotel utilize big data and advanced analytics to understand their guests and accurately target them with valuable offers? Simply put, it takes a team effort.
The hotel industry traditionally operates with siloed management structures, making it is easy to lose sight of the entire guest experience. It is vital that major departments within a hotel (sales, marketing, and revenue management) converge to work together. A hotel marketing team may be typically tasked with directly connecting with consumers to generate demand, while the revenue management team controls hotel demand through profitable pricing strategies. This can lead to disconnect in the direct and indirect messages coming from a hotel. Working together allows marketing and revenue management teams to complement each other. Revenue management can pinpoint areas of priority for demand generation, while marketing can communicate with the customers they need to fill those voids.
Capturing the Right Guest, at the Right Rate
The hospitality industry will never stop evolving, and 2016 will be another year of change with the landscape becoming more dynamic and more challenging. Today’s survival means that hoteliers have to take a more holistic, strategic approach to how they collect, analyze and action their data sets. In an age of increased competition, an increasingly fragmented booking environment and overwhelming amounts of actionable data, it will take the entire team – not just one department or group – to capture the right guest, at the right time, for the right rate.