Guest Influence on Revenue Management
Correlations Between Guest Reviews and Rate Positioning
By Michelle Woodley President, Preferred Hotels & Resorts | October 12, 2014
Revenue Management has been defined as ensuring the sale of the right room to the right customer at the right time for the right price. The hotel industry has matured in this area by developing data sets, methodologies, and programs to assist in achieving the goal of revenue and profit optimization. The robustness of the data available today and the processing speed of technology have allowed us to do this faster and more methodically. At the same time, our guests also have increased access to data, more tools to research the marketplace, and the ability to voice their opinions publically. It has come time for us to consider the tools available to our guests and their influence on our pricing and revenue management tactics.
Hospitality Revenue Management has traditionally been based on the following core inputs:
- Historical Data - at a minimum, we use past occupancy, average daily rate, and revenue. More advanced models include length-of-stay patterns, attrition factors, and lead time.
- Trends - the historical data helps to reveal day-of-week or seasonal patterns.
- Market Segments - in its basic form, this means transient and group. Typically, we further break down the segments to more defined like-user groups such as corporate transient, leisure individual, association group, social group, etc.
- Channel Distribution - the channels through which the segments book and through which the hotel wants to distribute the room product, and the cost of the distribution.
- Pricing Strategy - by segment and by channel; pricing structure, such as floating from, best available rate, or fixed or a hybrid.
- Pace / Demand - a look at how far in to the future are guests booking, what external factors such as local or regional events are driving the need for hotel rooms, etc.
- Cost per room
Companies have created products to provide us with various data sources and others have created programs to automate the depositing and processing of the data. This allows us to synthesize the data faster and make quicker decisions to ensure optimal business and profit.
Rarely was perceived value considered part of the equation. Rather, guests of loyalty programs and frequent travelers used their own experiences to make decisions about returning and, perhaps, how much they would pay. Other customers, however, were not privy to the thoughts and perceptions of fellow travelers.
Guests Empowered with Information
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