Revenue Analytics’ ideas and client successes have been profiled in leading periodicals. In addition, we work closely with the academic community to advance the state of the art in Revenue Management.
Learn more about Revenue Analytics’ philosophy and capabilities in the articles below. Topics range from creating and building a Revenue Management practice to honing Revenue Management capabilities by adopting powerful demand forecasting and performance measurement techniques.
SmartMoney profiles Robert G. Cross, Revenue Analytics' Chairman & CEO
In its May 2008 issue, SmartMoney magazine profiled Robert Cross as an innovator who has introduced price optimization to hundreds of companies.
Revenue Analytics' Jon Higbie quoted on cover of Hotel Business
"Carlson is innovating faster than most of its competitors in the sphere of Revenue Management at the moment - they have built forecasting as a true competency, rather than a technology. This enables them to deliver money-making insights to their hotels."
- Jon A. Higbie, SVP & Chief Scientist, Revenue Analytics, Inc.
"Is the Price Right?" Roundtable
Implementing best practices in pricing, including how price optimization can increase revenue and boost profit margin.
Competing on Analytics
Applying analytics across the enterprise, to maximize revenue and profit margin.
Customer - centric pricing: The surprising secret for profitability
Segmenting customers by analyzing customer purchase behavior and target prices to specific customer segments.
Pump Up the Revenue
Utilizing Revenue Management and demand forecasting methods to identify specific market segments and set optimal prices.
A Comparison of Unconstraining Methods to Improve Revenue Management
Comparing demand forecasting methods utilized in traditional Revenue Management companies and identifying which techniques generates the greatest increases in revenue.
The “Killer Application” of Revenue Management: Harrah’s Casino
Sophisticated Revenue Management techniques have allowed the casino to segment customers based on willingness-to-pay, forecast the demand by segment and make optimal decisions.