In her post last week, Natalie introduced the topic of integrating analytic approaches across departmental boundaries, and elaborated on the potential benefits to marketing from integrating analytic outputs from the revenue management department. This week, I’m going to take a look at the other side of that coin – considering the value of analytics originating in marketing to support improved and expanded revenue management capabilities.
The function of the revenue manager in today’s hotel environment is primarily to drive improved profitability by managing pricing, overbooking, and rate availability through a variety of available distribution channels. To accomplish this Revenue managers must coordinate with a number of other functions (including marketing and sales), and consider both methods to increase revenues (including room and ancillary products and services), and control distribution charges.
In supporting these decisions, revenue managers are often limited to making decisions at a market segment level. Today’s marketers, though, can take advantage of analytics that consider the willingness to pay of the individual – the result of careful targeting and tracking of promotions. What can revenue management do with this information? By combining analytics from marketing and revenue management, revenue management can have access to each customer’s purchase history, preferences, etc. – in addition to remaining available room inventory, forecast demand by segment and channel, and so on. This is a powerful set of tools for making a broad set of decisions!
One of the richest opportunities that revenue managers have taken to using this combined set of information is in the booking site. As noted above, revenue managers are increasingly interested in both improving revenues and controlling distribution costs – and the right kind of improvements to the hotel booking site can produce both of these benefits, as it is generally the lowest-cost booking source. An important criteria for measuring the productivity of a booking site is its propensity to turn visitors into bookers (the “look-to-book” ratio). The easiest and fastest way to improve “look-to-book” ratios is to ,make discounts available on the hotel booking site, however offering discounts indiscriminately runs the risk of eroding revenue, and should not be the preferred method for revenue managers.
From their normal forecasting processes, revenue managers knows when there are excess rooms to sell, and when there aren’t. By using that information, along with customer-specific information noted above, revenue managers can tailor the response from a customer’s booking query. Booking sites typically return multiple booking options – they are designed to provide several alternatives, which is a natural extension of turning “lookers” into “bookers”. By looking closer at individual customer preferences and purchase history, and combining this information with forecasting information from revenue management, it is possible to provide a responses and real-time offers that consider both the real value of a booking (on a particular date, and by room type), and each customer’s preferences. The result is a more efficient booking engine that maximizes both the value of the booking to the property, and the probability of their acceptance – all within the context of a low-cost distribution source.
By combining these analytics from revenue management and marketing, the best overall assortment to show the customer can be determined: an assortment that maximizes the expected value each visit to the site by each customer – considering their preferences, current booking levels, rates and discounts, and remaining demand. When customer purchase history information includes information regarding ancillary spends, 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.
Integrating both sets of analytics in the booking process helps to improve look-to-book by anticipating the responses (dates, room types, amenities, etc.) 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. However, integrating revenue management and marketing analytics to support these approaches can be challenging. This level of integration cannot be undertaken until the departmental systems that provide the basis of the information are available, and the information from them is “clean” and can be readily integrated into a real-time process. A flexible booking engine that can manage intelligent assortments, sorting, and offers is also required.
Before I close out our discussion on integrating analytics, I want to refer back to Natalie’s piece from last week. In her piece, Natalie referred to marketing’s dual objectives of nurturing and stimulating demand, and how revenue management analytic output can be used to guide stimulation activities. Accordingly, it is important to recognize revenue management’s role in this process to not only identify weak booking periods, but to also identify and communicate the underlying reason for the weakness: is this a normal, seasonal pattern? Or is this due to some outside factor? Is this expected to be a short-time impact, or are some longer-term affect (economy, competitive changes, etc.) in play? Accurate diagnosis and communication between revenue management and marketing will ensure that the appropriate actions are taken to improve the demand situation.
When revenue management and marketing share analytic approaches and coordinate activities, analytics can help an organization reach new levels of effectiveness – and drive impacts to the bottom line in ways unavailable in single-department approaches.