Estimated Incremental Revenue

Definition

How much net tuition revenue did paid media help generate? This page carries the extra applications from paid media through to dollars — by applying the enrollment yield and the average net tuition revenue of a graduate student.

The chain is simple:

extra applications → extra enrollments (via yield) → extra revenue (via net tuition)

Tip

The bottom line: In FY2025, paid media is estimated to have generated about $3.1 million in net tuition revenue. This is a planning estimate, not audited financials — but it translates marketing activity into the number a board cares about most.

Summary

Paid media generated an estimated 559 extra graduate applications in FY2025. Carried through the institution’s own enrollment yield and net tuition figures, that comes to roughly $3.1 million in net tuition revenue.

Step	Value	Source
Extra applications from paid media	559	Estimated Incremental Applications
× Enrollment yield (applicant → enrolled)	21.8%	enrolled tag, FY2025
= Extra enrollments	~122	calculated
× Average net tuition (graduate)	$25,582	institutional assumption, FY2025
= Extra net tuition revenue	~$3.11M	calculated

Note

FY2025 is the year we can model cleanly: it is the year the net tuition assumption covers, and its enrollment yield is reliable (see the maturity note in Methodology). FY2026 is not yet modeled here because its paid figure is dominated by the young EDDY cohort still moving through the conversion window.

Key Insight

Paid media paid for itself many times over. In FY2025 it generated an estimated $3.1 million in net tuition revenue from ~122 enrollments that likely would not have happened otherwise. Against any realistic paid media budget, that is a strong return — and it is built entirely from the institution’s own numbers: our applications, our yield, our net tuition. The next step is to divide this by actual spend to state a hard ROI ratio.

Why This Is Important

Application counts persuade an enrollment team; dollars persuade a board. This metric is the bridge. It takes the incremental-applications estimate — already grounded in observed behavior — and expresses it in the one unit every trustee understands.

It also sets up the two questions that close any budget conversation:

• ROI ratio — divide this revenue by paid media spend. If we spent, say, $500K to generate $3.1M, that is a 6:1 return.
• Cost per enrollment — divide spend by the ~122 incremental enrollments to get a defensible cost-per-incremental-enrollment figure.

Both require only one number we do not yet have in the data: actual paid media spend. Everything else is here.

Methodology

The estimate multiplies three quantities, all for FY2025 graduate students:

1. Incremental applications (559) — from the Estimated Incremental Applications page. This is the number of applications associated with paid media above the non-exposed baseline rate.
2. Enrollment yield (21.8%) — the share of FY2025 applicants who carry the enrolled tag in persons_dashboard (applicant → enrolled student).
3. Average net tuition revenue ($25,582) — the FY2025 graduate figure from marketing_revenue_assumptions, an institutional planning assumption.

incremental_revenue = incremental_applications × yield_rate × avg_net_tuition_revenue
                    = 559 × 0.218 × $25,582
                    ≈ $3.11M

Note

The enrolled tag gives a stable applicant-to-enrolled yield across all years (FY2023 30.6%, FY2024 20.0%, FY2025 21.8%, FY2026 23.8%), unlike a status-derived proxy which understates older cohorts once confirmed students matriculate and their status changes. FY2025’s 21.8% is used here because it is the year the net tuition assumption covers.

Caution

Assumptions and limits — read before quoting the number.

• Estimate, not audited revenue. Every input carries uncertainty; treat this as an order-of-magnitude planning figure.
• Incremental applicants are assumed to enroll at the overall applicant rate. If paid-media applicants yield differently than the average applicant, the enrollment figure shifts.
• Single revenue year. The net tuition assumption exists only for FY2025 graduate students, so revenue is modeled for FY2025 only. Add assumptions for other years to extend it.
• Graduate only. All persons in this dataset are revenue_group = graduate. A mixed-level institution would blend resident, non-resident, and regional net tuition figures.
• Net tuition, not gross. The $25,582 is net of institutional aid, so this already reflects discounting.

Query

WITH yield_fy25 AS (
  SELECT
    SUM(CASE WHEN applied = 'Yes' THEN 1 ELSE 0 END) AS applicants,
    SUM(CASE WHEN applied = 'Yes' AND enrolled = 'Yes' THEN 1 ELSE 0 END) AS enrolled
  FROM persons_dashboard
  WHERE fiscal_year = '2025'
),

inputs AS (
  SELECT
    559 AS incremental_applications,   -- FY2025, from Estimated Incremental Applications
    (SELECT enrolled * 1.0 / applicants FROM yield_fy25) AS yield_rate,
    (SELECT avg_net_tuition_revenue
       FROM marketing_revenue_assumptions
      WHERE fiscal_year = 2025 AND student_group = 'graduate') AS net_tuition
)

SELECT
  incremental_applications,
  ROUND(yield_rate * 100, 1) AS yield_pct,
  net_tuition,
  ROUND(incremental_applications * yield_rate, 1) AS incremental_enrollments,
  ROUND(incremental_applications * yield_rate * net_tuition, 0) AS incremental_net_tuition_revenue
FROM inputs;