Short answer: start with commercial auto or general liability policies (typically higher limits) and homeowner’s or renter’s policies for premises and dog bite claims — those two signals carry the most weight before anything else in this article. A perfectly clear liability case with no confirmed insurance behind it is still a hard case to monetize, which is why coverage type is one of the most commercially important scoring inputs.
Score Inputs & Weighting
- Commercial auto or general liability policies (typically higher limits)
- Homeowner’s or renter’s policies for premises and dog bite claims
- Uninsured or underinsured motorist exposure
- Multiple policies stacking (employer + personal, for example)
Where This Sits in the 0–100 Model
Confirming coverage type early, even when the visitor only ‘believes’ the at-fault party is commercially insured, lets the score reflect realistic recovery potential rather than treating every case as equally collectible.
This factor sits alongside Injury Severity as a Scoring Variable in PI Intake and Time-Since-Incident: Why Timing Changes Case Priority in the Lead Scoring Methodology cluster, and connects forward to How Instant Case Evaluation Increases Consultation Show-Up Rates in Conversion & Intake UX.
FAQ
Does this replace a human decision on lead scoring methodology?
No. It narrows down what a human reviews first. Signals like these route a submission into a priority tier; a staff member still makes the final call before a case is accepted.
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