Customer Case Study     BRIDGEi2i helps a premier US university to be predictive in identifying applicants and     student...
Customer Case Study     Intervention Strategy Development     We supported the client to identify specific     triggers th...
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BRIDGEi2i Case Study - Student retention strategy

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BRIDGEi2i helps premier US University predict and identify applicants with higher risk of dropouts. This helped the customers build an effective and timely retention strategy. More about BRIDGEi2i at http://www.bridgei2i.com

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BRIDGEi2i Case Study - Student retention strategy

  1. 1. Customer Case Study BRIDGEi2i helps a premier US university to be predictive in identifying applicants and students with higher risk of drop out and build effective & timely intervention strategies. Business Challenge The client organization is a leading US university with 10,000+ students in variety of programs across Science, Arts, Management, Nursing, etc. The university spends significant resources & effort on student reach out, awareness programs and admissions process to attract the best and suitable talent to the university. It is also financially critical that students stay through the period, since it impacts state funding to the university and also results in unutilized capacity within a program. The University was very keen to identify the drivers of early attrition and to identify profiles of students with high dropout risk so that appropriate interventions can be planned in a timely manner to maximize retention. BRIDGEi2i Solution Predictive models were built leveraging advanced statistical methods that help not only select applicants with a higher retention propensity but also identify students with a significantly higher risk of dropping out. BRIDGEi2i also identified key variables and triggers from both application and course performance data that will enable the university to design and implement effective intervention strategies aimed at maximizing retention. Key Drivers of Drop out Performed in-depth analysis of all applicant and student related data and information to identify the most significant parameters that affects retention. Predictive Retention Models BRIDGEi2i developed couple of statistically robust predictive models that predicts high risk applicants and identifies “at-risk” students at various points of lifecycle. One of the models was useful to identify such applicants who might leave within 3-6 months’ time and the other one helped to identify drop outs at the end of first year based on their performance and engagement during the first semester.For more details contact us: enquiries@bridgei2i.com Information Insight Impact© BRIDGEi2i Analytics Solutions
  2. 2. Customer Case Study Intervention Strategy Development We supported the client to identify specific triggers that help development of targeted intervention strategies aimed at improving retention Business Impact An illustrative simulation exercise by the university estimated an annual saving in the tune of USD 180K due to incremental retention. About BRIDGEi2i BRIDGEi2i is an analytics solutions company partnering with businesses globally, helping them achieve accelerated outcome harnessing the power of data. BRIDGEi2i helps companies to BRIDGE the gap between INFORMATION, INSIGHT and IMPACT in their journey to institutionalize data driven decisions across the enterprise.For more details contact us: enquiries@bridgei2i.com Information Insight Impact© BRIDGEi2i Analytics Solutions

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