For VP Enrollment Management
Forecast, retain, and benchmark in plain English
VPs and Vice Provosts for Enrollment Management use Clema to forecast enrollment, model retention, benchmark peers against IPEDS, and pull Pell, CDR, and PSEO data in one conversation.
How Clema helps
The enrollment questions you own, answered in minutes.
Forecast in plain English
Ask for a term-ahead enrollment forecast or a program-level yield prediction. Clema runs the model and shows the drivers, so you can stress-test scenarios without a data-science team.
Model retention and graduation
Get at-risk student lists with the factors behind each score. Target interventions where attendance, GPA, or course combinations are dragging completion.
Benchmark against IPEDS peers
Build peer groups and compare enrollment, retention, graduation, finance, and faculty. Every figure shows the federal source and year, board-ready.
The Tuesday before cabinet
Without Clema
You walk into cabinet with numbers that are already five days stale.
It's the Tuesday before the enrollment management cabinet meeting, and you need an updated fall census-versus-SEM-plan variance by college and by residency status. IR is three days behind because the president's office asked for a reformatted version of last week's pull first.
It's not that IR is slow:
- Typical ad-hoc fulfillment runs 3 to 14 days, per the whitepaper study.
- IR capacity climbs to 75-90% utilization in September, January, and May, exactly your census, packaging, and yield-reporting months.
- You're competing for the same three or four people every other VP is emailing that week.
With Clema
Same Tuesday, same cabinet meeting. You open Clema and ask for the census-versus-SEM-plan variance by college and residency status yourself. The answer comes back sourced to your live SIS data, with the method shown, before you've finished your coffee.
IR isn't cut out of the loop; they still own the definitions and the data model. What changes is that a question you can ask in plain English no longer has to wait in a queue behind everyone else's September request.
The old way vs. the Clema way
Same enrollment questions, a very different wait.
Situation
Old way
Clema way
Enrollment forecast for cabinet
Old way
Email IR, wait 3 to 14 days, get a static spreadsheet built around last cycle's assumptions.
Clema way
Ask in plain English, get the forecast with drivers shown, adjust the assumption yourself in the same conversation.
IPEDS peer benchmarking
Old way
Track down who built the last peer list, hope the methodology notes still exist, wait for a refreshed pull.
Clema way
Ask for the comparison directly. IPEDS source and year are shown on every figure, no hunting for the original methodology.
Pell utilization vs. discount rate
Old way
File a one-off request that queues behind everything else IR is already fielding during packaging season.
Clema way
Ask financial aid and Pell questions directly against live data, before the next award letter batch goes out.
Clarifying a follow-up question
Old way
Send a second email, wait again. The whitepaper found 73.5% of ad-hoc requests need 2 to 5 rounds of back-and-forth before they're answered.
Clema way
Ask the follow-up in the same thread and get an answer in the same conversation, no new request, no new queue.
Not a black box
Real models, evaluated on real held-out student data, not a demo dataset. See the full predictive analytics capability.
Term-to-term retention
"A model evaluated on 276,519 unseen student-term records achieves roughly 86.6% accuracy and 91 to 92% recall on the held-out test set."
Read the retention model deep diveGraduation within 150% time
"A model evaluated on 36,000 unseen students from a six-year institutional dataset, reaching approximately 0.911 AUC."
Read the graduation model deep diveAn enrollment leader's conversation
The enrollment management cabinet needs the fall census variance and Pell retention read locked before Tuesday.
Example figures for this walkthrough · Pell recipient share, first-time full-time
| Cohort | Your share | IPEDS peer median |
|---|---|---|
| Fall 2021 | 31% | 32% |
| Fall 2022 | 33% | 32% |
| Fall 2023 | 36% | 32% |
Example figures for this walkthrough · Most recent cohort, term-to-term
| Program area | Pell retention | Non-Pell retention | Gap |
|---|---|---|---|
| Program area A | 71% | 80% | 9 pts |
| Program area B | 69% | 79% | 10 pts |
| Institution-wide | 78% | 81% | 3 pts |
The enrollment picture is getting harder to read, not easier
Six independent reports point to the same conclusion.
3.9M → 3.4M
Projected US high school graduates, 2025 to 2041, about a 13% decline. Only ten states are projected to grow over that window, and the South is the only region with a net increase. That's the applicant pool most SEM plans were built against.
WICHE, Knocking at the College Door (11th ed.)56.3%
Average first-time, full-time discount rate for 2024-25 (51.4% across all undergraduates). Across 286 participating private nonprofit institutions, grant aid covered 63% of tuition and fees for first-time students; 83.4% of all undergraduates received some grant aid. Every point of discount rate is a decision made with less margin for error.
NACUBO, 2024 Tuition Discounting Study74%
Chief academic officers seriously worried about federal student aid changes. 65% are also very or extremely concerned about international enrollment amid visa and immigration policy shifts. Leaders described their role as more about fixing problems than planning ahead, citing lack of data and delayed decision cycles.
Inside Higher Ed / Hanover Research, 2025 CAO survey19.4M
Total US college enrollment for fall 2025, up 1.0% year over year. Enrollment is volatile even as the demographic cliff approaches, exactly why a single static forecast built once a year stops being good enough.
Chronicle of Higher Education, IPEDS-based Almanac"Outdated systems, disconnected teams, and blind spots in data"
How AACRAO frames the underlying SEM problem: a fragmentation and visibility issue, not a missing tactic or a lack of urgency on any one team's part.
AACRAO, Strategic Enrollment Management research41%
Top research priority for enrollment leaders is the "last mile" from admit to matriculation. That last-mile work depends on the same cross-functional, high-quality data that's hardest to get fast during peak season.
EAB, 2025 Enroll360 surveySmaller applicant pools, higher discount rates, and policy uncertainty add up to one thing: enrollment leaders need faster, more granular answers than a quarterly dashboard refresh gives them. That's the gap Clema is built to close.
Your busiest months are also IR's busiest months
Enrollment reporting peaks in September, January, and May, exactly when census counts, financial aid packaging, and yield reporting all land at once. Across the 50+ institutions in our whitepaper study, IR utilization climbs to 75-90% in those months, the same window your forecasts and benchmarking requests depend on.
Read the whitepaperWhere Clema fits with your SEM stack
Clema isn't another dashboard competing with Slate, EAB, or your SIS for attention. It sits on top of the systems you already run as a conversational layer, with a source and method shown on every answer. Your CRM stays the system of record for the funnel; your SIS stays the system of record for enrolled students.
Clema
Ask across the funnel and enrolled students in plain English, sourced.
Your systems
Federal datasets, built in
82.4%
of IR/IE teams cite data fragmentation across multiple systems as their top infrastructure issue. Adding another standalone system only makes that worse.
"The issue is not the absence of tools; it's the absence of integration."
Clema is how you ask a plain-English question across both without waiting for someone to build a new report. Every answer stays governed by your existing role-based access and SOC 2 and FERPA compliance.
What Clema gives your team
Forecasted
Term-ahead enrollment and yield, drivers shown
Modeled
Retention and graduation risk, at-risk lists included
Benchmarked
Against IPEDS peers, source and year shown
Enrollment leader FAQs
Yes. Clema builds enrollment forecasts and yield predictions in plain English on your historical data. You ask for a term-ahead or program-level forecast and get the model output with the drivers shown, not a black box.
Clema runs term-to-term retention and 150%-time graduation models on your student data. You get at-risk student lists with the factors behind each score, so your success teams can intervene where it matters.
Yes. Clema queries IPEDS in plain English, so you can build peer groups and compare enrollment, retention, graduation, finance, and faculty with the federal source and year shown on every figure.
Yes. Clema has built-in federal datasets including Pell Grant, Cohort Default Rate, PSEO, and College Scorecard, so enrollment and aid questions can pull public and private data in one conversation.
No. Clema doesn't replace your SEM plan or your existing forecasting methodology, it runs those models faster and makes the outputs queryable in plain English. If your team already has a validated forecasting approach, Clema can execute it on live data and let you interrogate the drivers; it doesn't impose a black-box model in place of judgment your team already trusts.
Student-level data, including Pell status, financial aid detail, and academic records, stays governed by your institution's existing access controls and FERPA obligations. Clema is built with SOC 2 and FERPA compliance as a baseline, and every query respects the same role-based permissions your team already has in the source systems, so a query never surfaces data a user wasn't already entitled to see.
Clema connects to your SIS, data warehouse, and BI layer, along with public federal datasets like IPEDS, College Scorecard, Pell, EADA, PSEO, and Cohort Default Rate, so answers reflect current data rather than a quarterly extract. The exact refresh cadence depends on how your systems sync to the underlying warehouse, which your IR/IT team controls.
Yes. Every answer Clema gives is sourced: it shows the dataset, the year or term, and the methodology behind the figure, the same audit trail an IR analyst would document by hand. That matters for board reporting and accreditation self-studies, where a number without a traceable source gets challenged.
Onboarding timing depends on your data infrastructure, but institutions typically plan a setup window ahead of one of the three peak reporting months (September, January, May) rather than during one. Talk to your IR/IE team and book a demo to scope a realistic timeline against your next census, aid-packaging, or yield-reporting cycle.
Pricing is published and free to start. The Free plan is $0 forever and includes 20 AI conversations a month for one user; Pro is $99 per month and Max is $299 per month, both available monthly or annually with two months free. Enterprise is custom annual pricing for institution-wide rollouts. Book a demo for a plan scoped to your team's size and data footprint.
Answer your enrollment questions in minutes
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