PREDICTIVE ANALYTICS IN HIGHER EDUCATION NOVEMBER 6, 2014

Transcription

1 PREDICTIVE ANALYTICS IN HIGHER EDUCATION NOVEMBER 6, 2014

2 WHAT IS PREDICTIVE ANALYTICS? Predictive Analytics helps connect data to effective action by drawing reliable conclusions about current conditions and future events. Gareth Herschel, Research Director, Gartner Group Predictive analytics: Enables businesses to use predictive models to exploit patterns found in historical data to identify potential risks and opportunities before they occur.

3 PREDICTIVE ANALYTICS APPLICATIONS IN HIGHER EDUCATION Retention Advancement Recruiting Budgeting and Planning

4 PREDICTIVE ANALYTICS APPLICATIONS IN HIGHER EDUCATION Retention Advancement Recruiting Attract high performing students Optimize recruiting spend Optimize financial aid spend Budgeting and Planning

5 PREDICTIVE ANALYTICS APPLICATIONS IN HIGHER EDUCATION Retention Identify at-risk students Reduce transfer and attrition rates Advancement Recruiting Attract high performing students Optimize recruiting spend Optimize financial aid spend Budgeting and Planning

6 PREDICTIVE ANALYTICS APPLICATIONS IN HIGHER EDUCATION Retention Identify at-risk students Reduce transfer and attrition rates Advancement Identify likely donors Understand likely donation amounts Preferred contact channels Identify high value donors Affinity to the university Recruiting Attract high performing students Optimize recruiting spend Optimize financial aid spend Budgeting and Planning

7 PREDICTIVE ANALYTICS APPLICATIONS IN HIGHER EDUCATION Retention Identify at-risk students Reduce transfer and attrition rates Advancement Identify likely donors Understand likely donation amounts Preferred contact channels Identify high value donors Affinity to the university Recruiting Attract high performing students Optimize recruiting spend Optimize financial aid spend Budgeting and Planning Forecasting enrollment Forecasting demand by major and course

8 A FEW FACTS ABOUT SPSS MODELER Predictive Analytics Workbench Graphical Menu driven Highly scalable solution from desktop to enterprise with server software No programming required Compatible with many other products Cognos BI Cognos TM1 Deployable anywhere from running manually ad-hoc to real-time scoring and integration with operational systems Many Databases Excel Other SPSS Products and more Depending on version, can handle unstructured (e.g. text) as well as structured data

9 IBM SPSS MODELER WITHIN THE BUSINESS ANALYTICS ECOSYSTEM Predictive Customer Analytics Acquire Grow Retain Predictive Operational Analytics Manage Maintain Maximize Predictive Threat & Fraud Analytics Monitor Detect Control Data Collection Social Media Analytics Statistics Modeler Analytic Server & Catalyst Analytical Decision Mgt Collaboration and Deployment Services IBM Research Watson Etc. 9

10 IBM SPSS MODELER PREDICTIVE ANALYTICS WORKBENCH

11 DEMONSTRATION PREDICTING WHO WILL RESPOND TO A MARKETING CAMPAIGN We ll use data about the past to build a model we can use to predict future outcomes Before we dive in, let me describe our exercise We have existing data on customers from a retail company s CRM system: Demographic data age, marital status, region, income, Purchasing behavior visits, purchases Segment customer segmentation Marketing campaign response (known, past behavior) We can bring data into SPSS Modeler from a variety of sources. In this example we ll bring the data in from an SPSS Statistics file. We ll use this data to build a model that predicts customer response to a marketing campaign After we build a predictive model, we ll score a different set of customers against the model to predict which of them are most likely to respond to the marketing campaign

12 QUESTIONS?