CourseAdvisor Forms Data Mining Group to Increase Enrollments at Postsecondary Schools

Data mining is a tool being used throughout higher education. This article introduces a group recently formed by CourseAdvisor to identify prospective students. CourseAdvisor is co-presenting their approach with Eduventures through a webinar on Thursday, June 21, 2007. See the article below for more details.

CourseAdvisor, a marketing and lead generation company that operates one of the top online education directories (OED), today announced a newly formed Data Mining Group. The group works with educational institutions to learn more about their course offerings and understand the ideal profile for a successful enrollee. By employing advanced data capturing and filtering techniques to the institution’s inquiry data pool, the group identifies ideal prospective students – those with a high propensity to apply and enroll – and tailors the school’s campaign to target them. This process results in improved conversion rates of leads-to-enrollments. The announcement was made today at Career College Association Convention & Exposition.

Read more

Netflix Prize Still Awaits a Movie Seer

Since its inception Netflix has employed analytics to drive growth and increase their competitive advantage. Lasf fall they launched a contest, seeking the brains and skills of analytics gurus outside their company. The goal: improve the accuracy of the existing Cinewatch movie recommendation system. The prize: $1 million.

The following article from the New York Times provides a summary of the contest results to date. Details about the contest are available at Netflix Prize.

Sometimes a good idea becomes a great one after it is set loose.

Last October, Netflix, the online movie rental service, announced that it would award $1 million to the first person or team who can devise a system that is 10 percent more accurate than the company’s current system for recommending movies that customers would like.

About 18,000 teams from more than 150 countries — using ideas from machine learning, neural networks, collaborative filtering and data mining — have submitted more than 12,000 sets of guesses. And the improvement level to Netflix’s rating system is now at 7.42 percent.

Read more