This article is part one of a three-part series on revenue management.
Data is changing the way hotels approach revenue management—for the better. This year will see hotels engage in greater sophistication when implementing revenue-management strategies, and increased usage of that information will allow hotels to better target previous and new guests in terms of marketing.
The maturity of machine learning is impacting revenue management now, said Nor1 CEO Jason Bryant, by allowing the monetization of personalization to hotel guests. “The tools are now available to allow commodization with revenue management,” he said. “Big data tools allow much more possible in terms of RM than in the past. More and more hotels are leveraging predictive analytics and getting good benefits out of it.”
Total revenue performance across all hotel revenue streams is steadily advancing, and by understanding the most profitable guests hotels can drive their most profitable business. This practice is challenging for hotels because using different transaction systems can make it difficult to aggregate data, according to experts.
As hotels invest more in their technology, and the people and processes accompanying that technology, there is a greater ability to manage all generated revenue through a single revenue-management system, said Sanjay Nagalia, COO for IDeaS Revenue Solutions. “We are getting closer to being able to drive transient guests to the most profitable booking channels through personalized offers, based on how guests shop and spend,” he said. “Similarly, providing transparency of existing demand and its value will soon be applied to group, meetings and events.”
Using this type of business intelligence is the next big technology advance for revenue management, said Dom Beveridge, EVP of demand generation for the Rainmaker Group. “Business-intelligence systems are the key to asking why demand isn’t what it traditionally is,” he said. “BI systems can help me find a marketing solution for my RM outcomes.”
Beveridge said business-intelligence systems are the trend behind the trend—revenue-management systems predict the future demand trends. Business intelligence can enable users to understand causality and act while there’s still time to impact demand for a future arrival date.
Imagine, for example, a hotel whose future demand is generally lower than expected for some future period. This trend would first be predicted by demand forecasting—a revenue-management process. It would then fall to revenue management to make the pricing decisions that will optimize predicted revenue based on predicted demand. In the case of a shortfall in demand, the general trend would be for prices to fall. But dropping price is not always the right thing to do, Beveridge said. And that’s where revenue management and business intelligence intersect.
A recent Hospitality Sales & Marketing Association International survey, “Portrait of Revenue Management Leadership,” asked which strategic change would be the most important within revenue management over the next three years. Moving beyond revenue management to predictive analytics was the choice of 40 percent of respondents as the most important strategic change in their area over the next three years. Nearly one-quarter (24.4 percent) selected fully integrating revenue management with sales and marketing. Aligning revenue management with IT was selected as the least important strategic change among revenue leaders.