This true cost per lead case study shows what CDAI (Capital, Decision, Accuracy, Intelligence) calculates for 8 simulated businesses. Each business ran as a simulation, so the correct answer was known for every figure. Then the numbers were checked two ways, and two more runs used real HubSpot and Salesforce accounts.
An ad platform tells you what you paid the platform. Then it divides that by leads. That is the platform’s cost per lead.
However, a lead costs more than media. For example, a partner may keep a share of revenue. Also, a refund or a chargeback may reverse a sale. A vendor may charge a fee too. In short, all of those belong to the lead.
So CDAI divides every cost by the number of leads. That is the true cost per lead. Dividing the same true cost by sales gives the true customer acquisition cost (CAC).
Each row is one simulated business, shown on its own numbers. Also, nothing is added together across businesses. The gap is how much higher the true figure is than the platform’s.
| Simulated business | Days | Leads | Platform CPL | True CPL | Gap | True CAC |
|---|---|---|---|---|---|---|
| Roofing contractor | 90 | 2,263 | $8.77 | $99.97 | +1,040.5% | $488.64 |
| Independent insurance agency | 81 | 807 | $19.87 | $39.07 | +96.7% | $437.87 |
| Residential solar installer | 90 | 1,483 | $21.13 | $63.47 | +200.4% | $672.28 |
| Senior-living placement advisor | 150 | 1,937 | $21.99 | $34.02 | +54.7% | $306.46 |
| Mortgage originator | 105 | 1,087 | $38.88 | $43.01 | +10.6% | $453.86 |
| Personal-injury law firm | 120 | 1,827 | $33.02 | $54.34 | +64.6% | $554.68 |
| Clinical-trial recruitment business | 210 | 1,542 | $48.40 | $48.40 | +0.0% | $956.76 |
| Deliberately unhealthy stress test | 150 | 7,407 | $34.01 | $145.67 | +328.3% | $4,333.20 |
Simulated data. Seed 1 of three simulated worlds per business. Gap = true CPL versus platform CPL. The full report shows all three seeds for every business.
The gap changes with the business. Where partners, refunds and fees are large, the platform number understates the cost by a wide margin. Because of that, a campaign can look cheap in the ad account and yet lose money. The clinical-trial recruitment business is the control: its only cost is media spend, so its true and platform figures match at $48.40. The engine adds a gap only when a cost exists.
Over 90 simulated days, the roofing contractor generated 2,263 leads and 463 sales. The ad platforms alone would have reported $8.77 per lead. The true cost per lead was $99.97.
Then the table shows where the rest of the cost came from. Every dollar is a cost the simulated business actually carried.
| Cost layer | Amount | Share of true cost |
|---|---|---|
| Media spend | $19,836.40 | 8.8% |
| Partner payouts | $12,364.00 | 5.5% |
| Refunds | $158,319.53 | 70.0% |
| Chargebacks | $35,719.88 | 15.8% |
| True cost | $226,239.81 | 100.0% |
True CAC for this business was $488.64. This is what the business produced in the simulation. However, no decision was acted on, so it measures the business, not an uplift from the engine.
A case study is only worth reading if the arithmetic is right. So the numbers were checked in two independent ways.
In addition, the database was reconciled to the simulated world line by line. Unexplained differences: 0. Our 30-day retest methodology explains how outcomes are graded.
Two of the 26 runs used real developer accounts. One ran on a real HubSpot portal and one on a real Salesforce org. The simulation created the leads and won deals in the real CRM. Then the nightly adapters pulled them back.
A verifier compared the real CRM with the engine’s database record by record. HubSpot passed 14 of 14 required checks. Salesforce passed 14 of 14. In both runs the fingerprint of the CRM’s won-deal list was identical to the database’s.
The runs also found a defect, so we named it and published it. For example, when a CRM deal and a payment charge both describe one sale, the engine stores it twice. The full report prints the exact counts.

Instead, the point of the exercise is narrower. It tests that the engine’s arithmetic is right on worlds where the answer is known. See the full validation report for per-decision results.
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