Observed Pre-Payment Subscription Risk methodology
What CheckoutSignal captures
CheckoutSignal documents the pre-payment checkout flow of a site: how a user arrives, what they do, when pricing and recurring terms are shown, and where consent is requested. Each profile is built from at least one captured run with ordered screenshots.
Where we stop
CheckoutSignal stops before payment submission, wallet authentication, card entry, and consent-checkbox submission. It uses synthetic files and personas only. On every profile we show whether payment was submitted (no) and whether cancellation was tested. Any step not reached is listed under "what was not tested".
Route labels
We prefer normal user ingress (a Google ad or organic click) and label the route honestly. When Google blocks automated search, we switch to a documented fallback and label it as such. A compound route (for example, organic arrival plus a separate profile for the upload continuation) is described in the profile's route note.
How scores work
The Subscription Clarity Score is a weighted 0–100 measure across eight fixed criteria. Each criterion carries a 0–5 severity; the overall score is the sum of (severity ÷ 5 × weight), scaled to 0–100.
| Criterion | Weight |
|---|---|
| Subscription vs one-time clarity | 25 |
| Renewal price & frequency clarity | 20 |
| Visual prominence of recurring terms | 15 |
| Consent & CTA clarity | 15 |
| Trial / free / low-price framing | 10 |
| Express-checkout risk | 5 |
| Free / lower-cost path clarity | 5 |
| Seller support & cancellation visibility | 5 |
The Subscription Clarity Score measures observed pre-payment subscription clarity. It does not determine whether a company violated the law.
Current MVP profiles show DRAFT scores. Severities were assigned from the run reports as a modeling step and have not yet passed human review. A higher score means more observed subscription-risk signals, not a legal finding.
Evidence layers
Raw screenshots are kept immutable and separate from extracted observations, evidence pins/annotations, rubric evaluation, and public narrative. Annotations reference screenshots by ID and (when captured) a normalized region; they never modify the image.
Language
CheckoutSignal describes observed subscription-risk signals. It does not call sites scams, fraud, or illegal, and does not determine whether a company violated the law. Corrections and company responses are always free.