Industries · Education
Value-Based Bidding for Education: Bid on Enrolments, Not Inquiries
A prospectus request and a serious application for a full degree both count as one lead. Your admissions data knows which inquiries enrol, and for how much. Estimate what each new inquiry is likely to be worth from your own enrolment history, so bidding learns to find students rather than form fills.
Why lead counts fall short
Why a count of inquiries misses what an enrolment is worth
Education funnels are long and leaky. Inquiries become applications, applications become offers, offers become enrolments, and at every step most drop away. An ad platform told only about inquiries will buy whichever kind is cheapest, which is usually the least committed.
Your admissions records show the pattern. Some programmes enrol far more often from an inquiry; some study modes and start terms convert better; fees range from a short course to a full degree. That is the signal the platforms need, and the one they never see unless you send it.
Enrolment rate and fee move separately
Short online courses often enrol quickly and often at a modest fee; degrees enrol rarely at many times the price. Expected value weighs both.
Applications are an early signal
An application often arrives within days of the inquiry. Where your history shows it reliably does, the product can use it to raise a lead's value while Google still accepts the change.
Price on what is recorded, not lifetime
The product prices on the fee your records hold for an enrolment, such as first-year or full-course tuition. It does not predict whether a student continues into later years.
The funnel
From inquiry to enrolled
- Inquiry
- Application
- Offer
- Enrolled
Known when the lead arrives
What a new lead can be priced from
- Programme of interest
- Study mode, online or on campus
- Intended start term
- Funding route, self-funded or employer-sponsored
Learned later
What the history is trained on
- Whether an application followed
- Whether an offer was made
- Whether the student enrolled, and the fee
The programme, study mode and start term on the inquiry are what price a new lead. The application, offer and enrolment are what the history is trained on.
How it works
From your sales history to what the ad platforms see
- 1
Bring in your history
A CRM export or a HubSpot connection: leads with their outcomes, won, lost or still open.
- 2
Find what relates to value
Each field known when a lead arrives is tested against your closed deals. Only the ones that clearly moved outcomes are kept.
- 3
Estimate each new lead
Its expected value: how likely leads like it are to become customers, times what those customers were worth.
- 4
Send the value
To Google Ads or Meta, as a conversion value on the lead. Sending changes no bid by itself.
- 5
Judge it on real outcomes
Compare closed deals before and after your campaigns start optimising on the values, never the values we sent.
Worked example
Three leads, three different values
Expected lead value = the estimated chance of becoming a customer × the expected value of that customer.
Value basis: First-year tuition. The fee recorded on the enrolment. If your records hold the full course fee instead, that is the basis, and the values mean the same thing in those terms.
Part-time MBA, employer-sponsored
- Start: next intake
- Study mode: blended
8% × $32,000
$2,560
estimated value of this lead
Online certificate
- Start: next month
- Self-funded
25% × $3,200
$800
estimated value of this lead
Undergraduate prospectus request
- No start term given
- Study mode not chosen
2% × $27,000
$540
estimated value of this lead
Illustrative example, not customer results.
The MBA inquiry is worth about three times the certificate and nearly five times the undergraduate request, whose fee is almost as large. What the inquiry says about intent matters as much as the programme.
How the product actually estimates this
It does not score each lead on its own. It starts from your overall close rate times your average won deal, with any deal above three times the median counted at that cap, then applies a multiplier for each field that clearly moved outcomes in your history, and rescales so the average estimate matches what your leads were actually worth. Fields that do not clear the evidence thresholds are left out and listed. The formula above is the same idea in one line.
What data you need
Your CRM already has most of it
- Inquiry dateWhen the inquiry arrived, not the start of term.
- Enrolled, not enrolled or still openInquiries that never applied or declined an offer are as useful as enrolments.
- Fee on enrolmentsFirst-year or full-course tuition, consistently one or the other.
- Fields from the inquiry formProgramme, study mode, start term and funding route, as the inquirer gave them. No age, nationality or other personal characteristics.
- Matching informationGoogle's click ID or the inquirer's email for Google; email or phone, plus Meta's cookies from your site, for Meta.
What matters most is reliable outcomes and enough of them. The report checks your own file and names anything it could not price, rather than applying a one-size minimum.
How activation works
Estimating, sending and optimising are three steps
The product estimates each lead's value and sends it. Your campaigns use it only once you set them to optimise for value, a change you make in the ad platform, and the platform decides when an account qualifies.
Google Ads
Sends each inquiry's estimated value to a conversion action in Google Ads, matched on the click ID or on email. A reliable early stage such as an application can raise that value within Google's 7-day window. Campaigns use the values only once they bid on value.
Switching a live campaign, step by stepMeta
Sends a ValuedLead event with the value through the Conversions API. Website-form ad sets bid on values once they qualify for value optimisation; instant-form ad sets can learn from application and enrolment stages through Conversion Leads.
How the Meta route worksThe full method, from pricing a lead to measuring the result, is in the complete guide. Leads that reach your CRM without a click ID are covered in the click ID guide.
How to judge success
Measured in outcomes, not in the values we sent
Enrolments per inquiry
By programme, before and after the switch.
Cost per enrolled student
Ad spend against enrolments, not against inquiries or prospectus requests.
Applications per inquiry
The earliest honest read, weeks before enrolments are known.
Reported conversion value going up is not the result; it repeats what we sent. The product's evaluation compares enrolments before and after the switch, with inquiries from other sources as a control.
Questions
Education, specifically
Our intake happens twice a year. Does that break the model?
No, but it shapes it. Leads are judged against inquiries from the same point in the cycle, and the start term is tested as an input. Include at least one full year so both intakes are in the history.
Can we use age or nationality to price inquiries?
No. Age and national origin are protected characteristics, and the product refuses them by column name. Programme, study mode, start term and funding route are the fields to use.
Should the value be first-year tuition or the full course?
Either, applied consistently. Full-course fees favour long programmes more strongly; first-year fees are closer to cash in the door. The product does not predict drop-out or continuation.
We sell short courses and degrees. One model or two?
One, with the programme as an input. It prices the difference where your enrolments show one, and caps any fee above three times your median so the biggest programmes cannot dominate the signal.
Check whether your lead data is ready
Upload a CRM export or connect HubSpot. In about five minutes you see which of your fields relate to value, what new leads would be estimated at, and whether your history is enough to send. The file is read in your browser; you are asked for a name and work email before the full report.