For most hotel companies, rooms are the primary, and most profitable, revenue source.  Information about stay patterns, booking channels, room type preferences, geographic preferences and any interaction the customer has with your firm can provide insight about behavior, which leads to better promotion and pricing decisions.

Advanced analytics uses this detailed customer behavior data for: 

• Microsegmentation to identify statistically significant subsets of customers with similar preferences and purchase behavior: e.g. eco-conscious families with children under ten that travel in the summer and prefer to stay in the west or southwest. 
• Market basket analysis to identify “missing” products:  e.g. customers who stay with you as a business traveler, but never for leisure. 
• Social network analysis to find customers who influence other travelers behavior: e.g. every time a certain corporate customer stays at your property, he or she brings three other customers from the same company
•  Liklihood to respond to determine which offers should be sent to which customers
• Lifetime Value Calculations to identify the most valuable customers
• Cross-sell/Up-sell to determine which add-ons or upgrades to offer to which customers

When this powerful information about the customer is integrated with demand patterns and price sensitivity analysis from revenue management (described below), proactive demand sourcing becomes a reality. 

Advanced Analytics for Revenue Management

Revenue managers are responsible for setting rate and availability controls such that revenue is maximized across the enterprise.  In the hotel industry, where rooms revenue is the primary revenue source, revenue management focuses on this highly profitable stream.  In the casino industry, gaming revenue is a primary focus, and the hotel rooms support the gaming revenue.  Many hotels and casinos are also beginning to move towards total asset profit optimization, where revenue streams from all ancillary outlets, including gaming and hotel rooms, are considered in the revenue management decision.  Regardless of the approach, the limited capacity of hotel rooms is carefully managed in order to increase property-wide revenue and profits.  The increasing sophistication of revenue management technology and revenue management practice provides continued opportunities for advanced demand analysis. 

Careful analysis of demand patterns by location, date, room type, length of stay, market segment, channel, and rate, as well as competitor price and positioning provides a comprehensive view of demand and enables advanced analytic applications like:

• Contract evaluation to determine the optimal pricing for contract business
• Rate rationalization to determine the optimal mix of rates and rate plans for transient demand
• Channel management to know what prices and products to offer on which channels and when to open and close these channels
• Revenue Opportunity Modeling to track the performance of revenue management programs, comparing actual results to the theoretical optimal
• Non-traditional revenue management to apply revenue management techniques to non-traditional outlets like meeting space, golf, restaurants, theater tickets and spa.

Integrated Marketing and Revenue Management Analytics: The Next Frontier

Armed with advanced intelligence from each function, the integration of the two becomes even more powerful.  Deep insight about customer behavior combined with strong analysis of demand patterns across the system provides the opportunity to:

• Incorporate total customer value in the RM decision: optimize property-wide revenue by considering the total customer spend profile beyond the room rate (or gaming revenue)
• Promotion demand forecasting: incorporate expected lift from promotional activities into demand forecasts for an accurate picture of the impact of incentivizing demand
• Create dynamic packages: Allow the guest to choose the elements of the package, and then price the entire package appropriately based on forecasted demand for all components.  Suggest alternate times and dates which would push demand to slower periods, while providing a lower cost option for the guest
• Next best offer: While guests are exploring your website or speaking with your agents, using the guest profile or searching behavior combined with pricing from the revenue management system, encourage conversion by creating an offer designed just for them.  For unknown customer, browsing behavior on the website compared with experience with previous customers can provide the basis for an offer that they are most likely to accept, and revenue management data provides a profit-maximizing price
• Cross-Sell/Up-Sell: Find opportunities to cross-sell or up-sell products based on customer preferences and the optimal price for those products based on demand. 

Rom Hendler, VP Strategic Marketing, The Venetian Resort-Hotel-Casino, says “It’s more important than ever to join customer relationship management and revenue management to maximize profitability. Combining data mining and revenue optimization tools helps the Venetian allocate rooms effectively – based on the potential profitability of each customer and the opportunity cost of the room.”

Consider this scenario:  Revenue management alerts marketing that demand is soft during weekends in February for leisure travelers for suites at the city center hotel in Philadelphia.  The system has determined that up to a 20% discount off of the weekend rate would still maximize revenue for those weekends.  Marketing reacts by developing a promotion that targets customers who are likely to book at that price during that time period, and stimulates just enough demand to fill the empty rooms.  Promotional details are sent back to the revenue management system which automatically incorporates the expected lift into the revenue management forecast. 

Or this scenario:  A customer is browsing your website for Caribbean properties, paying particular attention to diving and restaurants.  While the customer is browsing a message pops up offering a package at the Turks and Caicos resort including six hotel nights, a dive trip, and dinner at the resort’s new restaurant featuring the Caribbean’s hottest chef.  The pricing for the package come directly from the revenue management system, with date ranges that maximize the property profitability.  A link to a video featuring underwater footage of divers off of the island shore is also provided.

Without accurate intelligence from each department, these scenarios are simply not possible.  Working together, marketing and revenue management can transform the organization from reactive to proactive, forming deep and lasting relationships you’re your customers while maximizing property-wide profits.

About the Author

Kelly A McGuire, PhD

Kelly McGuire is the product marketing manager for SAS Institute’s gaming and hospitality practice.  In this position, Kelly is responsible for communicating the value of SAS solutions to the gaming and hospitality market, as well as working with product management, sales and research and development to ensure that solutions meet the needs of the market. 

Kelly has 18 years of experience in the hospitality industry, both in operations and in information technology.  Before joining SAS, Kelly consulted with Harrah’s Entertainment to develop restaurant revenue management strategies for the casinos in their major markets.  Kelly was a senior consultant at Radiant Systems, working with contract food service clients on web-based administrative solutions to manage cash handling, inventory management, supply chain and labor.  She also worked for RMS (Revenue Management Solutions) on menu-item pricing strategies for chain restaurants, and designed a function space revenue management system for the Westin in Singapore.   Kelly’s operations experience is primarily focused on the restaurant industry, although she has worked in hotels and casinos.  She managed an upscale Creole restaurant in New Orleans, and was the general manager of a franchised Ben and Jerry’s Ice Cream Shop in the French Quarter. 

Kelly has a BS from Georgetown University and a Master of Management in Hospitality from the Cornell School of Hotel Administration.  She also has a PhD from The Hotel School, focused on non-traditional applications of Revenue Management.  Her dissertation was on the impact of occupied wait time on customer perceptions of the waiting experience.  Her research has been published in the Cornell Hospitality Quarterly, and she has conducted a number of executive level seminars on capacity management and non-traditional applications of revenue management.