Helping companies in various industries to solve difficult pricing problems, SAS (News - Alert) has introduced SAS Revenue Management and Price Optimization Analytics.
SAS Revenue Management and Price Optimization Analytics is an analytic package that facilitates the development of proprietary revenue management and price optimization capabilities.
By utilizing advanced revenue management and price optimization demand modeling and forecasting techniques, this product assists in improving revenue.
SAS Revenue Management and Price Optimization Analytics automatically incorporates price factor of demand for a product into forecasts. Helping users to become the brand of choice among investors and stakeholders, early adopters can now witness enhanced competitive positioning and an improved revenue stream.
The flexible and tailored delivery approach can also decrease change management, apart from offering the state-of-the-art benefits that can be obtained with customized revenue management solutions. Maintaining current workflows and user interfaces, this new product allows companies to select and introduce a new system.
Alternatively, focusing on an existing system can allow them to upgrade just the analytics. According to the company, this flexibility is not available in off-the-shelf offerings.
“SAS has redefined revenue management. By injecting new analytical techniques, using more data and leveraging faster processing power, SAS magnifies the advantage of forecasting and optimization,” said Kelly McGuire, executive director, Hospitality and Travel Global Practice at SAS. “This empowers companies to boost revenue lift more than is possible with traditional revenue management analytics.”
Recently, the company introduced new software for rapid paced companies that require immediate insight from real-time data streaming into their enterprises. By continuously analyzing data as it is received, the new SAS software allows real-time decision making.
The new software is a form of complex event processing (CEP) technology used for important data management and analytic applications and analyzes high-volume "events in motion.”
Edited by Braden Becker