COMPETITIVE INTELLIGENCE TOOL (EMCIT TM ) Recruitment Goals: Sample - - PowerPoint PPT Presentation

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COMPETITIVE INTELLIGENCE TOOL (EMCIT TM ) Recruitment Goals: Sample - - PowerPoint PPT Presentation

Using Segment Analysis Service Data to Recruit, Enroll, and Retain the Right Students COMPETITIVE INTELLIGENCE TOOL (EMCIT TM ) Recruitment Goals: Sample University Goal 1: Build the prospect pool Goal 2: Build the low/no discount pool


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SLIDE 1

COMPETITIVE INTELLIGENCE TOOL (EMCITTM)

Using Segment Analysis Service Data to Recruit, Enroll, and Retain the Right Students

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SLIDE 2

Recruitment Goals: Sample University

  • Goal 1: Build the prospect pool
  • Goal 2: Build the low/no discount pool
  • Goal 3: Build the pool of academically

strong students

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SLIDE 3

Competitive Intelligence and SAS

  • Start with top 5 feeder clusters (both HS and EN)
  • Look at cluster descriptions to narrow down to a few Priority Clusters
  • Focus EPS reports on Priority Clusters in order to address goals
  • Identify 10 new, promising recruitment markets
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SLIDE 4

Sample University: Cluster focus

EN Cluster Defining Characteristics

78

Wealthy; Financial aid is not a priority; Choose good schools, a number of which are private and religiously-affiliated; Median income is $134K

51

Relatively high income; Students tend to take AP and honors courses and have above-average test scores; Median income is $95K HS Cluste r Defining Characteristics 72 Predominantly Christian affiliated schools; Serve upper middle class communities; Students exposed to above average curricula; Strong test scores

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SLIDE 5

EN Cluster 78 Neighborhoods

  • These neighborhoods contain the types of students who are most likely to

be interested in Sample University and vice versa.

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SLIDE 6

Priority Cluster Focus: EN 78

Geomarket Name Geomarket Code Total Test Takers Sample U Score Senders Montgomery Metropolitan MD02 3447 Fairfax Co VA02 3303 30 Fairfield Co CT03 3226 20 Westchester Co NY15 3079 3 Essex Co MA04 1408 Fulton Co GA02 1289 35

  • GA02 has a large number of 2015 test takers living in EN 78
  • Sample U has had some success there
  • Sample U has a strong alumni base in Georgia and could build on

their prior success

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SLIDE 7

GA 02 Focus by Zip Code

2014 % Living in EN 78 % Living in EN 51 ZIP Code Total Test Takers 30350 55 64% 10% 30328 1140 37% 5% 30342 73 34% 13% 30345 831 24% 19% 30338 609 21% 7%

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SLIDE 8

GA02: Focus on HS 72

HS Name State Country Geomarket Code Total Test Takers Sample U Score Senders Landmark Christian School GA US GA02 72 Fellowship Christian School GA US GA02 61 12 Mount Pisgah Christian School GA US GA02 56 3 Loganville Christian Academy GA US GA02 40

What is Sample U doing differently at Fellowship Christian? Have they been recruiting at Landmark Christian?

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SLIDE 9

Competitor success in EN 78

  • Pick top 7 competitors (SAT overlap /

NSC)

  • Look at their success in the Priority

Cluster

  • Compare that to Sample U’s success
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SLIDE 10

Competitor success in EN 78

2014 Score Senders Sample U Comp1 Comp2 Comp3 Comp4 Geomarket Name Geomarke t Code

Austin & Central Texas TX06 4 30 47 25 87 Fairfax Co VA02 30 28 38 48 17 Fairfield Co CT03 20 12 38 49 9 Fulton Co GA02 35 96 389 96 4 Lowell, Concord, & Wellesley MA08 5 14 18 3 Montgomery Metropolitan MD02 28 79 70 7 Southwest Houston Metro Area TX16 3 20 50 37 127

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TX16 Drill-down

2014 Total Test Takers % SAT > 1200 % Out-of- state Mobility % Living in EN 78 HS Name Duchesne Academy of the Sacred Heart 60 50% 63% 30% Emery Weiner School 63 27% 67% 76% Episcopal High School 171 27% 68% 51% Kinkaid School 143 58% 80% 55% Memorial Senior High School 632 37% 54% 51% Saint John's School 148 79% 93% 40% Saint Stephen's Episcopal School Houston 7 29% 29% 29% Saint Thomas Episcopal School 38 66% 55% 39%

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SLIDE 12

Be More Data-Driven with SAS

  • Be more targeted with name buys = Save Money!
  • Build presence in new markets wisely
  • Spend precious travel dollars in the right places to find the right

students for you

  • Segment Analysis data can help at all stages of the funnel / student

cycle

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SLIDE 13

Full-cycle use of SAS data

  • We incorporate these data into:

– Inquiry-to-applicant conversion model (EMPOWRTM)

  • Combine SAS factor scores with institutional data
  • Can greatly expand what we know about inquiries

– Predictive yield model (EMFASYSTM)

  • Especially helpful with non-aid filers

– Predictive model of retention

  • Incorporate SAS into admit strategy to choose students most likely to

succeed

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SLIDE 14

Emily Coleman

Vice President for Enrollment Management Services

Maguire Associates, Inc. 978.371.1775 Ext. 258 ecoleman@maguireassoc.com www.maguireassoc.com