Graduate School Admissions Data
GRE/GMAT scores, GPAs, and admission outcomes by program -- the data that grad school applicants need to calibrate their chances and that AI advisors use to recommend schools.
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Find Me This Data →Overview
What Is Graduate School Admissions Data?
Graduate School Admissions Data comprises standardized test scores (GRE/GMAT), GPAs, and admission outcomes that prospective graduate students use to evaluate their candidacy and compare themselves against accepted cohorts. This data is critical for applicants calibrating their chances of admission across different programs and institutions. Educational technology platforms, AI-powered advising tools, and recruitment analytics firms actively use these datasets to provide personalized school recommendations and help institutions understand competitive admission profiles within their programs.
Market Data
20% more than bachelor's degree holders
Master's Degree Earnings Premium
Source: Encoura
11% increase overall
Graduate Enrollment Growth (Past Decade)
Source: Encoura
Down 30% in 13 years
Graduate Enrollment Rate Decline
Source: Encoura (Current Population Survey analysis)
Sagged 0.3% year-over-year
Fall 2025 Graduate Enrollment Change
Source: National Student Clearinghouse Research Center
5.9% decline in fall 2025
International Students in Graduate Programs
Source: National Student Clearinghouse Research Center
Who Uses This Data
What AI models do with it.do with it.
Graduate School Applicants
Prospective students use admission statistics (scores, GPAs, acceptance rates) to assess their competitiveness and identify target schools aligned with their profile.
AI-Powered Advising Platforms
Educational technology companies and AI advisors leverage historical admissions data to generate personalized school recommendations and predict admission likelihood.
Graduate Admissions Offices
Enrollment and admissions teams use comparative program data to benchmark their cohort profiles, adjust recruitment strategies, and understand market positioning.
Education Analytics Providers
Consulting firms and research organizations analyze admissions trends to help institutions model enrollment scenarios and optimize recruitment strategies.
What Can You Earn?
What it's worth.worth.
Program-Level Admissions Datasets
Varies
Pricing depends on scope (number of programs, years of data, GPA/score granularity) and exclusivity
Aggregated Benchmarking Data
Varies
Institutional subscriptions and licensing models vary by data provider and depth of analytics
Real-Time Admissions Intelligence
Varies
API access and feed pricing scales with query volume and update frequency
What Buyers Expect
What makes it valuable.valuable.
Accuracy and Currency
Data must reflect actual admission outcomes from recent cohorts; outdated statistics reduce value for applicants making current decisions.
Comprehensive Score Coverage
Complete GRE/GMAT score distributions, GPA ranges, and demographic breakdowns allow users to accurately position themselves against accepted students.
Program-Level Granularity
Data segmented by specific degree programs (MBA, MS Engineering, MA Literature, etc.) is more actionable than institution-wide aggregates.
Outcome Transparency
Clear documentation of acceptance rates, enrollment outcomes, and time-to-degree helps users evaluate program competitiveness and value.
Companies Active Here
Who's buying.buying.
Aggregate program data and provide applicant-facing tools for school selection and admission probability estimation
Train recommendation algorithms and personalized guidance engines using historical admissions patterns
Benchmark cohort profiles, model recruitment scenarios, and refine domestic and international student targeting strategies
FAQ
Common questions.questions.
What specific data points are included in Graduate School Admissions datasets?
Datasets typically include GRE and GMAT score distributions (quantitative, verbal, analytical writing), undergraduate GPAs, acceptance rates, enrolled student demographics, and sometimes employer outcomes or time-to-degree metrics. Program-level granularity is essential for actionable insights.
How current must admissions data be to have market value?
Admissions data is most valuable when it reflects recent cohorts (within 1–2 years). Since applicants make decisions based on current program competitiveness, outdated statistics lose relevance quickly. Real-time or annually refreshed data commands higher demand.
Who are the primary buyers of this data?
Primary buyers include AI-powered advising platforms and school-search tools (serving applicants), graduate institutions' enrollment and marketing teams, and education analytics consulting firms that help schools optimize recruitment and admissions strategies.
Why is graduate school admissions data valuable despite declining enrollment?
Even as overall graduate enrollment faces headwinds (down 30% over 13 years), individual programs and institutions remain highly competitive. Admissions data helps applicants navigate this tighter market by identifying realistic targets, and it helps schools refine recruitment to reach serious candidates earlier in the decision process.
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