SAS® predictive analytics, data mining named 2012 Trend-Setting Product
CARY, NC (22 Aug. 2012) – SAS® Analytics lets organizations anticipate business opportunities, helping combat fraud in financial services, speed drugs to market in life sciences, identify cross-sell opportunities in retail and much more. For its innovations turning data about customers, performance and financials into information for meeting challenges, SAS predictive analytics and data mining software from the leader in business analytics earned the KMWorld 2012 Trend-Setting Product of the Year Award.
"Using SAS Analytics, Monster Worldwide, parent company of Monster.com – the premier global online employment solution for people seeking jobs and the employers who need great people – creates and deploys predictive models that boost job postings performance," said Jean-Paul Isson, Global Vice President of BI and Predictive Analytics, Monster Worldwide and co-author of Win with Advanced Business Analytics (2012). “Leveraging SAS we marry external and internal data to deliver customer intelligence that makes our clients’ recruitment more effective. We saw sharp improvements. With global scoring and optimization models, our average order size increased 24 percent and retention jumped 17 percent. Innovation through analytics fuels those successes.”
Getting started with analytics
With a common platform and multiple entry points, SAS Analytics meets the analytics needs of different types of users. Key components include:
SAS recently expanded its family of high-performance analytics, helping customers create new value from big data - including text - to make better decisions within tight time frames. All SAS applications are backed by 24/7 support, comprehensive consulting and training to ensure maximum return from IT investments.
To learn more, see the video Manage the data deluge with data mining and predictive analytics or download the white paper Data Mining 101, which explains how predictive analytics and data mining improve business performance by revealing new insights from existing data.