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Yield Prediction & Aid Optimization


How can we better project and predict the likely enrollment outcomes for new students? 

How can we optimize our financial aid strategy to achieve our various enrollment and revenue goals for new students?
How can we better predict enrollment yield in response to our aid packaging strategy? 
How can we empirically model the tradeoffs we have to make across our multiple enrollment objectives – including quality, diversity, affordability and net revenue?
How can our financial aid approach be modified to better respond to the current economic crisis impacting families’ ability to afford our college?  
Is our current financial aid strategy sustainable in light of our enrollment demand, enrollment mix and competitiveness?


Financial Aid and Matriculation Analysis

A robust and statistically rigorous approach to yield prediction, segmentation and net revenue projection.


Aid Strategy Analysis

Evaluation of impact of alternative approaches to merit scholarship and need-based aid.

Segmented Affordability Analysis

Analysis of affordability by segments of student population vis-à-vis student need, unmet need gaps, family self-help, debt burden and long-term financial obligation.

Trade-off Analysis

Models to assess inter-related strategies to improve quality, diversity, affordability and net tuition revenue.

Differential Net Pricing by Program

Evaluation of approaches to differentiated net pricing for undergraduate, graduate and professional programs.

Slate Services

Includes custom development of real-time linkages of CRM data into yield predictions; integration of aid and admissions dashboards.

Survey Research

Custom surveys designed to complement yield predictions or to evaluate market response to aid packaging strategies.


Colleges shape their enrollment profile and net tuition revenue through their financial aid policies, practices and packaging regimen;  the impact on the bottom line is great as are the risks involved in estimating that impact. Appropriately rigorous statistical models can project and predict enrollment outcomes from alternative aid strategies in ways that mitigate those risks while optimizing not only enrollment yield and net revenue but outcomes in program mix, academic profile, competitiveness, affordability, diversity and retention. As such, aid optimization is not just technique; it is perhaps the clearest measurable manifestation of a college’s core values and priorities.

Want to talk more about how HCRC can help your college or university?
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