Advanced Revenue Management is all about following the people (guests) instead of the product (rooms). It therefore involves the application of mathematical techniques to PMS and POS data in order to classify guests into behavioral groups that better predict their booking and spending patterns. The intelligence from this guest analytics often debunks many long-held beliefs and renders irrelevant many of the metrics by which hotels have been measured for decades. Guest Analytics is the fuel that powers successful loyalty programs, marketing campaigns, experience management, and Total Revenue Management. However, transitioning to Guest-Centered Revenue Management is not an easy task for most hotel companies because the process involves not only more advanced data science skills, but also the cooperation of departments that may not be used to working together. Regardless of what type of hotel company you work for, here are the five hard steps you will have to take to get to more
Question everything you think you know. The hotel industry runs on guest classifications and performance measures inherited from a time when there was limited data and tracking the billing process was the priority. Guest analytics helps you measure your world using measures that matter. “Transient” and “Leisure” become less significant and labels based on guest’s behavioral tendencies take the driver’s seat. The dependence on Per Available Room (PAR) measures naturally diminish as you begin to measure your performance on Per Available Customer (PAC). This transformation will require hoteliers to accept having to re-learn the way they evaluate their business model and to discard time-honored, yet irrelevant performance indicators.
Your PMS and POS systems were designed to perform certain operational tasks efficiently and perhaps even offer you some traditional hotel reporting. These systems collect data to capture the “what” and never the “why”. To get closer to the latter, you must extract data and shape it so that it serves a new purpose – behavioral analysis. This requires you first, reconsider the way your systems are organized and then more critically, identify the bottlenecks which are preventing you from collecting the data you will now need. This sounds easier said than done, as data quality initiatives often challenge not only individual habits but the operations of the business as a whole.
Creating buckets or segments that identify the true profit value of each guest is the goal of Guest Analytics. Using the mathematics of Clustering, Similarity Analysis, and Probability Theory, you can create new guest categories that highlight behavioral patterns rather than billing processes. As an example, An “OTA” label tells you a lot about how the guest booked but nothing about how much they are willing to spend. However, a “Relaxation Weekender” tells you a lot about both. For a behavioral segment to be significant it must be valuable to RM and Marketing. RM should be able to identify and forecast the segment’s distinct booking and spend patterns. In addition, Marketing should be able to have access to this segment and to design unique offers for this them. This is where a Guest Analytics led hotel will develop synergies between RM and Marketing that a traditional PAR based hotel could never achieve.
With new tools by which to measure your world, you should retrace your steps. Create new performance measurements that are driven by guest behavior and then find the past decisions that have had an impact on changing guest spend. Looking at past financial performance based on your new buckets will also give you insight into what was worth doing and what did not matter. Often, great, expensive decisions have no effect on guest behavior. Conversely, the smallest changes can cause the most damage.
With your new categories you can also set new goals for customer service, revenue management, sales, marketing, F&B and ancillary performance. You can set new KPI’s that are focused on Total Guest Spend and not just “outlet-specific” spend. The calculation of ROI for everything from Marketing to Construction Projects changes dramatically. You will also be able to identify what touch-points really matter and which have little return. This will in turn drive more intelligent budgeting, forecasting, cost controls, and bonus structures.
Finally, you can begin to explore the option of offering your best guests unique rewards for their loyalty and advocacy of your brand. While recent research has shown that simple hotel loyalty programs usually become stale and die, the same studies reveal that those that are run on advanced Guest Analytics can stay “fresh”, relevant, and profitable.
The value of all the analysis in steps 1-4 begins to be realized when you power the daily decisions in your hotel with the new insights. By uploading your new, intelligent guest profiles into your PMS, POS, CRM, and Revenue Management systems, you allow managers to better understand and calculate the potential impact of their decisions. Employing the mathematics of optimization, you can prescribe to managers the course of action that is likely to yield the best outcome.
More important, intelligent guest profiles allow well trained, front-line employees to recognize opportunities for experience enhancing gestures. Companies like Ritz-Carlton have successfully embedded guest experience data into their operational systems to drive their “Mystique” standard. This is where you begin to establish a more intimate relationship with each guest through a more personalized stay.
Guest-Centered Revenue Management is much more than a technique, a measurement, or a system. It is a new way of thinking for hoteliers. This mindset is actualized as you engage in this 5 step process above. It will have huge implications for the way you manage your hotel and it is beginning to change the hotel industry as we know it.
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Robert Hernandez, Statistical Analysis and Data Mining for Revenue Growth Robert is an expert in the field of mathematical Hotel Optimization and Analytics. He has spent the last 17 years building data-driven forecasting and optimization models for companies in over 20 different industries, from tech to tourism. Robert possesses a very unique skill set including cross-disciplinary experience, advanced mathematical and analytics skills, data transformation, industry-specific knowledge and business-process improvement expertise. Robert began his career at the Walt Disney Company in Revenue Planning. Read More+