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Data Science Revolution

Data Science Revolution

Earlier this week, I was joined by Amber Toro, Director of Data Science here at enroll ml to discuss the Data Science Revolution currently happening within the world of admissions.  The recording is still available – but consider this the TLDW (too long, didn’t watch) webinar summary.



Lead Scoring Is Just A Profile


      • The concept of lead scoring is not without merit, but it does not contain the potential we have often attributed it to

      • Institutions that rely on lead scoring too much will miss out on potential enrollments

      • To be useful at directing recruiting effort, a scoring model needs to be quick, dynamic, and include signals from the individual student

    Your Yield Analysis Is Misleading You


        • Measuring the yield rates on a single variable provides some insights, but the conclusions can be misleading

        • In the example of campus visits, it can lead institutions to put effort in the wrong area

        • We fail by not measuring the relationships among variables

      Data Science Isn’t A Side Job


          • An institution can completely change the game by leveraging high-level data-science work, improving staff morale, yield, and enrollment in one fell swoop

          • An admissions counselor exploring CRM data on the side will never get to that point

          • Even worse, if an institution isn’t clear on the limits of counselor “research” – they can make incorrect decisions based on poorly designed analysis


        As a profession, we have overloaded the applicants per counselor ratio.  Data science can be an answer to identify the right students to reach out to on any given day.  In fact, it may be the only answer.  Getting it right can drastically change the fortunes of your institution.  Getting it wrong can lead to treading water, or worse, falling behind.

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