Online Service Promises Improved Enrollment Results

Noel-Levitz Recruits SAS^® for Data Mining and Information Delivery

With a new Web-enabled solution from SAS, admissions-consulting company Noel-Levitz is helping both public and private universities develop and implement sophisticated recruitment strategies faster than ever before.

Customer Success Video

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Tim Thein
Senior vice president,  Noel-Levitz

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Gary Fretwell
Vice President for Corporate Development,Noel-Levitz

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The Chronicle of Higher Education lists Noel-Levitz as an ideal partner for enrollment management solutions. And according to a study by the Core Group, an independent research organization, Noel-Levitz is the first place that colleges and universities turn to for outside enrollment advice. The company's results are visible in everything from improved enrollment numbers and academic profiles to increased student body diversity and net operating revenue.

For Noel-Levitz, the ideal partner for data mining and information delivery is SAS. Noel-Levitz uses SAS Enterprise Miner, a data mining solution, to deliver solid recommendations to its clients. New applications development technologies with .NET interoperability capabilities from SAS help the company deliver those recommendations instantly via the Web.

Targeted recruitment efforts
With a prestigious client list that includes The Ohio State University, Tulane University and the DeVry Institute of Technology, Noel-Levitz has helped more than 1,600 colleges and universities since 1973 with enrollment management issues, including student recruitment, financial aid and student retention, as well as staff development and strategic planning.

One of the company's most successful offerings has been ForecastPlus for Recruitment. Powered by SAS, this predictive-modeling solution provides accurate, statistical results that help universities increase their recruitment success. Additional ForecastPlus services focus on student retention and loan default prevention.

"It's very expensive for colleges and universities to actively recruit and follow students throughout the enrollment cycle," says Tim Thein, senior vice president at Noel-Levitz. "SAS helps us produce a model based on many enrollment factors, including location, academic ability, college major, estimated income level and more. From that, we create a relative score that accurately predicts which students are the right students for that university and their likelihood of enrolling in that institution." The ForcastPlus solution combines and models admissions data, census data and Equifax data, along with individual requirements from each university to meet specific enrollment and recruitment goals. With the ForecastPlus solution, universities can explore student data during three unique stages of the enrollment process:

• The prospect stage, where admissions officers can filter more than 250,000 students whose names have been purchased from list-providing services.
• The inquiry stage, which models a smaller group of students who have already expressed an interest in the university.
• The admissions stage, which examines data for all students who have been admitted into the university and predicts which of these students will actually enroll.

Online capabilities deliver instant results for customers
In the past, Noel-Levitz's clients typically waited two to three weeks for results from each of these models. Today, with the new Web-enabled capabilities of ForecastPlus, results are available instantly via a secure Web server. Clients can analyze student lists from anywhere – their offices, homes or hotel rooms – as long as they have Internet access.

The solution provides a unique score for each student, often identifying students who are up to five times more likely than the average student to enroll at that particular institution.

"We've created custom Web services that enable our clients to input their data, manipulate it and then submit it for scoring," explains Thein. Developed using SAS Integration Technologies, SAS/ACCESS to ODBC and .NET technologies from Microsoft, the custom-built solution makes it easy for clients to submit data and retrieve results from the same Web-enabled application.

SAS/ACCESSenables SAS solutions to read, write and update data regardless of its native database or platform, and SAS Integration Technologiessoftware lays a foundation for standardized communications and effective information distribution.

Noel-Levitz statisticians Jeff Easterling and Dan Edstrom save client data on a SQL server and build their recruitment models with SAS Enterprise Miner, SAS' award-winning data mining software. SAS Enterprise Miner sends results directly to the Web via SAS Integration Technologies, which Edstrom says saves a lot of time and money.

"Using SAS Integration Technologies and SAS/ACCESS to ODBC, we're able to have the Web service talk directly to SAS, and SAS is able to talk to our SQL server database, so everything works very well together and we don't have to transform information," explains Edstrom.

SAS offers advantage in marketplace
The new Web-enabled features of ForecastPlus represent a significant advantage for Noel-Levitz and its clients, says Thein. "Predictive modeling for college enrollment has become more competitive in the last few years. By investing resources in the Web-based scoring application, we can maintain an advantage in what has become a much more dynamic marketplace."

Elizabeth Herr, senior statistician, agrees. "None of our competitors will be offering these services online for a few years, so more and more schools will look at this as the way to get what they need faster."

And for many universities, faster results translate into improved recruitment efforts. "When you're competing with a dozen universities for the same students, being the first in the mailbox can be a big win," says Thein. "Our customers make very strong claims about this service saving them money by targeting the right people, providing enrollment gains and even helping increase revenue." And with the new Web-enabled capabilities from SAS, Thein and his team of statisticians are confident those claims will continue to grow.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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