Analytics, the 'Holy Grail' of Revenue Management
By Lily Mockerman Founder, Total Customized Revenue Management | March 12, 2017
Analytics are what some might call the 'holy grail' of revenue management. We build technology to try to capture them, seek new ways to apply them, and wonder how to use more of them. Dashboards and reporting suites are touted by vendors of all sorts as key to the value of their products. Meetings are driven with reports spread across a table or screen as various players on the team work to make sense of the numbers and what they mean for their business. Analytics help give us the information needed to relay suggestions to marketing, advertising and public relations teams to help identify areas that are currently experiencing success and others that may need improvement. They can be used to help predict consumer behavior and provide effective ways to use product availability and price to maximize a company's revenue growth. Using analytics as a foundation allows hoteliers to enhance their ability to shed light on how the guest will behave before, during, and after the travel planning process.
As is often discussed in leadership circles, the best predictor of future behavior is past behavior. The data analytics provides can be harnessed to predict future actions. Analytics are also imperative to forecasting both the subject's and the market place's pricing and product availability.
Big Data is the new hot button for analytics, with increasing conversation around how to harness and use it at the hotel level. Per an article from Forbes, Big Data can be seen as a collection of data from traditional and digital resources from inside and outside a company that can provide a source for continuous discovery and analysis.
Each individual guest will check into a hotel with their own set of expectations and preferences, and it has become the job of Revenue Managers to help identify areas of success and failure, so that hoteliers can achieve those expectations to deliver a returning customer. To do so, we must use in-depth data and resources to help us differentiate between customer preferences. However, despite our refrain of better use of analytics, we still misuse or ignore the basic capabilities we already have.
In the use of analytics, we see three primary issues:
1. Collection Addiction - When a company has a high level of focus on collection of data from multiple points but doesn't place enough emphasis on effective application, leaving them with a disjointed data warehouse of unusable metrics. Companies can gather an influx of data that may help tell a story, but if they don't have the ability to effectively apply the information, then it will be considered useless. This issue often presents itself when working with big data.
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