On the Q1 FY26 call, Walden grew enrollment 13.6% at a 32.6% segment EBITDA margin; Chamberlain grew 2.2%, its margin down 240 bps, and management put it bluntly: a September-intake miss on "local marketing effectiveness" and "funnel conversion." So two of your three brands are running visibly different marketing physics, and the only number that would settle it (cost-per-start by brand) lives bundled inside a single $247.4M advertising line, reported as one lump. The board will ask how much of three years of spend growth (219.4 → 227.9 → 247.4) bought new starts versus rode the tuition increase. These three tools are built to have an answer ready.
You do have one: a marketing-analytics function with the real per-brand spend in its BI stack. So the value here isn't a number your team can't compute; it's the two things an inside team is structurally bad at producing: an independent read that's allowed to conclude "spend less," and a spend frontier drawn inside the 90/10 + Gainful-Employment + FTC box, where which students you recruit is a compliance question, not just an ROI one. A black-box bid optimizer can't enter that room. A model whose every input is a citation can.
The cross-brand cost-per-start radar
The question it answers: if you split the $247.4M three ways the way your revenue splits, what cost-per-start does each brand imply, and where's the spread?
- Allocate the disclosed ad line across Chamberlain, Walden, and Medical & Vet; watch implied cost-per-start move live
- Cost-per-start shown as a bounded range, never a single disputed number: the honesty is the point
- Every anchor cites a 10-K cell; the one unknown (the real split) is labelled as the knob it is
The constrained efficiency frontier
The question it answers: where does the next marketing dollar buy the most qualified starts, once 90/10, Gainful Employment, and FTC rule out the moves a pure-ROI optimizer would make?
- Reallocate spend across brands and watch the efficient frontier move, with compliance flags that gray out the off-limits corners
- One click for each regime: pure-ROI, 90/10-safe, GE-safe: see how much "efficiency" the rules actually cost
- The independence wedge made literal: a recommendation that's allowed to say "shift less into the auction-priced funnel"
The EBITDA → enterprise-value bridge
The question it answers: what is a point of marketing efficiency on the $247.4M line actually worth, in EBITDA, and in enterprise value at your multiple?
- Move blended cost-per-start down N% at constant starts; see dollars freed flow to EBITDA near dollar-for-dollar
- Apply a 12-16x multiple to read the enterprise-value swing: the currency a board and a sponsor actually price in
- The durability switch: one-time diagnostic vs. quarterly instrumented cadence, because a read doesn't compound and a habit does
Priced as a diagnostic, never a subscription.
A fixed-scope, 4-6 week independent read that ships the working models above on your public filings, then scopes the internal-data extension: the real per-brand split and channel cost-per-start your stack already holds. The IP transfers. No platform, no seat licenses, no data leaves the building.
Why pay despite an in-house team → the independence & regulatory-defensibility math
The one-page engagement sheet → scope, timeline, and the ask, on a single printable page
This is a re-entry, not a cold pitch. Higher-ed enrollment marketing is where I started (same funnel, same lead-gen trade floor) and large-scale measurement is where I went. A solo specialist also carries no agency account-conflict and no incentive to grow your managed spend.
The prototypes are the meeting.
Synthetic per-brand allocation only, calibrated to cited public anchors; independent concept work, not affiliated with Covista. One 30-45 minute working session and I'll walk all three live on your own FY25 filings.