With a title like “doubling down on analytics,” it also seemed appropriate to “double down” on contributors. In the revenue management corner, we have Alex Dietz, Principal Industry Consultant for SAS’s Hospitality and Travel Global Practice, and in the marketing corner, we have Natalie Osborn, Senior Industry Consultant for SAS’s Hospitality and Travel Global Practice. This article is the product of their joint expertise and focus on improving analytics for the hospitality and travel industries.
As colleagues in SAS’ Hospitality and Travel global practice, we spend a considerable amount of time together discussing revenue management and marketing analytics. In recent years we have seen that marketing and revenue management teams are working together much more closely than they have in the past. Driven by the realities of the hyper-competitive market introduced by internet distribution, as well as the opportunities afforded by readily available customer data and inexpensive methods for distributing promotional offers, revenue management and marketing teams are now close partners in driving and managing demand.
But the opportunities for this collaboration extend well beyond what are generally considered best practices at this point. Through a deeper sharing of information and integration of departmental systems, marketing and revenue management can improve how they generate, manage and optimize revenues through the application of new techniques that would have been considered science fiction stories just a few years ago.
In this article we will review the roles of the marketing and revenue management functions discuss the importance of proper coordination between them – and provide some examples of what can go wrong when that coordination isn’t there. We’ll review the current practices that support this coordination, and then we’ll discuss in detail some of the opportunities for driving this coordination to a more operational model, supported by technology and analytics. Finally, we’ll discuss some of the challenges that stand in the way of this next generation model. As departments, marketing and revenue management are like two sides of the same coin. Marketing is responsible for brand awareness and demand stimulation including campaign strategies, customer relationship management and loyalty programs. Marketing owns the relationship with the customer, and understands and manages customer preferences, purchase behavior, customer value and which offers customers are most likely to respond to. On the other side of the coin, revenue management is responsible for managing demand, including setting price and managing availability. Revenue management owns the room inventory and measures price sensitivity and demand by property, market segment, and date – and uses this information to set rates and rate availability. They know when and where demand is expected and needed.
Marketers should be looking to stimulate demand and maximize the response rates from their offers and promotions. However, if marketers plan promotions without the guidance of revenue management, that promotion planning can damage the efforts of revenue managers as well as marketing. The classic example is when a marketing promotion is sent out for dates when the hotel is already forecasted to be at capacity – or, when the revenue manager is unaware when promotions are targeted for and incorrectly interprets demand changes that are the result of that promotion. In the first example, customer experience is impacted when customers call to redeem an offer or promotion and there are no rooms available. In the second example, the decisions of the revenue manager and even the revenue management system could be impacted by unexpected changes in demand patterns.
More and more companies are starting to act more collaboratively across marketing and revenue management, whether they are sharing information in a meeting format or sharing reports directly. Revenue managers produce demand and occupancy forecasts for their properties, whether aided by a revenue management system or by doing so manually. When marketers have ready access to these demand and occupancy forecasts, they can place promotions more effectively. Similarly, when revenue managers are made aware of when or where campaigns are being scheduled and the kinds of response rates expected from these campaigns, they better anticipate how demand is impacted, and are able to adjust demand forecasts proactively.
Sharing information is a great place to start, but one of the areas we at SAS are most focused on is how to better integrate the analytics outputs from marketing and revenue management. We have been exploring the benefits of giving marketers access to the same information that revenue managers and revenue management systems use regularly to make decisions. When choosing the best combination of campaigns upon which to execute, otherwise known as marketing optimization, what if marketers could include information from revenue management, such as the demand forecast, prevailing price, demand-to-come and occupancy forecast? What can marketers do with that information?
One of the best places to start is with promotions placement. Most revenue management systems forecast the unconstrained demand for each property on specific dates, as well as the constrained form of that demand, or occupancy forecast. Using the number of rooms forecasted to be unsold as a constraint, and the types of campaigns and response rates as decision variables, it is possible for a marketing optimization engine to select the campaigns and customer segments that stimulate the right amount of demand to sell the unfulfilled rooms at the right time and place. Another interesting opportunity occurs if the reach of revenue management also extends to creating demand forecasts for other areas of the operations, such as gaming, restaurants, retail, spa and or golf. Marketing could use these demand forecasts to prioritize which segments are stimulated so that promotions not only stimulate demand for rooms, but also stimulate increased demand for ancillary areas.
Lastly, if marketers have access to the prevailing price and price sensitivity information from revenue management, then they can manage promotion pricing more effectively overall. Marketers are responsible for nurturing demand, through creating and maintaining a brand image and identity that attracts regular demand. They are also responsible for stimulating demand, which is a more targeted approach for generating demand for very specific periods. Promotions and offers are tools that can be used for either approach; the main difference between the two is how targeted the offers are. When nurturing demand, marketers can rely on existing information regarding customers to help design promotions, such as what offers have been successful in the past. Price response information from revenue management may also be useful in evaluating the response of the overall customer base to a general offer. When stimulating demand for specific periods with targeted offers, incorporating information from revenue management can help ensure that any offers are not below a level that would cannibalize base demand or be rejected for availability by later revenue management decisions.
Revenue managers are always looking for how to drive the extra dollar in revenue, or how to save the extra dime in distribution charges – and they should. Unfortunately, revenue managers are often constrained by having to make decisions at a market segment level – while marketing gets to make offers that consider the willingness to pay of the individual, because they will be sending offers directly to them (and they track customer responses, of course). But what if revenue management had access to this same information? What if revenue managers know each customer’s purchase history (including customer spend not only on rooms, but on food and beverage, services, ancillaries, and so on), preferences, and ultimately their “lifetime value?” What can they do with that information?
Perhaps the best place to start would be to look at the booking site. Revenue management knows where (by date and room type) there are excess rooms to sell, and where there aren’t. This simple difference is typically captured by a good revenue management system in the quantifiable form of a “bid price” or “last room value” – the expected displacement cost of accepting another customer in that room type on that date. Using this value (and some pretty sophisticated analytics), revenue managers can tailor the response from a customer’s booking query. By doing this it is possible to provide a tailored response that considers both the real value of a booking (on a particular date, and by room type or even by property), and the customer’s preferences to maximize the value of the booking, and the probability of their acceptance.
Now remember, for those personnel that run booking engines, one of the most important criteria for measuring the success of the site is its propensity to turn visitors into bookers (aka the “look-to-book” ratio). Of course, offering discounts is a great way to improve look-to-book ratios – but that approach is often revenue-dilutive – it’s not the sort of thing that revenue managers want to be the first choice for moving customers to their site. Also remember that a booking site doesn’t typically return just one option – they are designed to provide several alternatives. But the approach outlined above has the benefits of helping to improve “look to book” by anticipating the responses (dates, room types, properties) most likely to be accepted by a given customer, and then combining this information with revenue management forecasts to help identify which responses are most valuable– to help drive up revenue – and including both in the alternative set shown to the customer (the assortment).
This approach can then be enhanced with targeted discounts that benefit both the customer and the property, for example:
- Suggesting a different night, at a discount – a discount that helps drive bookings away from heavy-stay nights onto low-occupancy nights, where the incremental booking is more profitable to the property, even if the rate to the customer is lower.
- Suggesting a different room type, at a discount – the customer may normally book a standard room, but offering an upgrade to a deluxe room at a nominal rate difference.
- Similarly, if there are multiple properties in the same market, the customer can be offered a different property – another win-win.
By using analytics, you can carefully judge the best overall assortment to show the customer: an assortment that maximizes the expected value of a booking by that particular customer – considering their preferences, available rates and discounts, and expected occupancy. If the customer purchase history information includes information regarding ancillary spends (food and beverage, casino spend, etc.), then this approach can augmented by giving preferred availability on full or shoulder days to customers with significant ancillary spend history, or adjusting the assortment display to include packages that match the customer’s preferences and history. The use of analytics in this manner is called assortment optimization. Assortment optimization is a field that has seen wide acceptance in the retail industry, but relatively little practical application in hospitality. Of course, there are barriers to implementing the type of approaches that we have outlined in this article; there’s a reason everyone isn’t doing this already.
First of all, there is a platform of various technologies that must be in place, including:
- Systems to capture, cleanse, and store customer information • Systems to segment customers based on demographics and purchase behaviors
- Systems to target customers for offers, and track and predict responses to these offers
In Revenue Management:
- Systems to predict demand and set market prices and manage rate availability
For the Enterprise:
- A booking engine capable of supporting customer-level offers and presentations
While many organizations have these pieces, there’s a great deal of optimization to these systems that can take place without considering the possibilities of integration between them.
Even with these systems in place, though, challenges remain. One challenge that we most frequently see is a mismatch in segmentation between marketing and revenue management teams. Such a mismatch is perfectly reasonable – each function has different needs associated with customer segmentation, and a segmentation method that has been optimized for marketing purposes will often prove to be a poor method for revenue management purposes – and vice versa. In order to move beyond this difference and into integration, systems need to pass information in a manner that can be consumed “on the other side.”
Another challenge relates to the specificity of offers, and the tradeoff between highly targeted offers (targeted to carefully “fit” the dates and places where demand is required), and offer complexity. Overly targeted offers tend to introduce significant complexity to offers, making them harder to understand, more difficult to “message,” and overall less “compelling” to the customer. Of course, from a revenue management point of view, under-targeted offers are simply revenue-dilutive. The art here is finding an appropriate balance that produces offers that are well targeted, compelling, and easy for your customers to understand and purchase.
Similarly, while the benefits of carefully targeted offers are clearly significant, it is important to recognize marketing’s role in establishing and maintaining a brand image that supports consistent long-term demand patterns. A marketing approach that leans too heavily on offers can have the impact of encouraging customers who make up your long-term demand to buy at a discount. If your brand image centers on being the lowest price provider, then this is a perfectly acceptable approach. However, using promotions and offers to stimulate long term demand will soon erode brand position in favor of a customer base that sees the brand only in terms of price.
Finally, an important role that the revenue management function must fill in this whole equation is to clearly communicate to marketing the difference between a short-term weak period and a larger market demand issue. As an example, a number of properties communicated to us late in 2012 a concern regarding “soft” bookings for the 2013 New Year – was this a temporary issue, or the tip of some larger iceberg? After a careful review of the market and interviews with sales staff, they determined that what they were seeing was the effect of Washington’s “sequester” standoff – not a short-term issue, but potentially a much larger issue that would impact overall demand patterns.
As colleagues focused on analytics for marketing and revenue management, we are excited about the possibilities for closer integration of analytics. Not only do decisions benefit the good of the enterprise, but there are analytic efficiencies to be gained from better integration between the two departments. When marketing has access to demand forecasts, there is no need to expend time and energies in creating their own. Similarly, when revenue management can understand the direct impacts of brand nurturing and demand stimulation efforts, they do not have to rely on the proverbial “cannon to kill the mosquito,” by using the lever of price alone.
When marketing and revenue management activities are synchronized at the data and analytics level, decisions are made considering the good of the enterprise, not just the good of each department. As the analytic approaches for both departments have evolved and continue to evolve, it is critical that hospitality enterprises take advantage of the opportunities for an integrated approach and avoid the pitfalls of decision making in siloes. Now is the time to start reconciling some of the differences between the two departments and pave the way to doubling down on analytics.
Alex Dietz is the Principal Industry Consultant for the SAS Hospitality and Travel Practice. Dietz is a 25-year veteran of pricing and revenue management solutions development and consulting in hospitality, travel, and retail. Before joining the Hospitality and Travel Practice, he worked as the Product Manager for SAS Markdown Optimization – a price optimization solution used by leading fashion retailers – a position he held with SAS for five years. Prior to joining SAS, he was Vice President of Revenue Management and Marketing for Raleigh-Durham based Midway Airlines from 1998 to 2002, reporting directly to CEO Robert Ferguson. Dietz began his career with American Airlines, where he managed the development of American’s industry-leading yield management systems. Following his time with American, he joined SABRE where he acted as product manager for SABRE’s airline revenue management solution and also led SABRE’s pricing and revenue management global consulting practice. In his various roles as consultant and solution developer, Alex has worked with leading airline, hospitality and retail customers around the globe. Dietz earned his MBA and BS (Industrial Engineering / Operations Research) degrees from Syracuse University.
Natalie Osborn is senior industry consultant for SAS Institute’s Hospitality and Travel practice, and an 18+ year veteran of hospitality and hospitality technology solutions development, specializing in analytics and revenue management. Prior to joining SAS, Natalie was the director, product marketing for Minneapolis-based IDeaS Revenue Solutions, where she worked from 2000 to 2011. She is a frequent contributor to industry publications, speaker at industry conferences and is coauthor of the SAS and Cornell Center for Hospitality Research blog “The Analytic Hospitality Executive.”