A lead scoring model is only as good as its feedback loop. If you can't trace which lead scores correlated with actual closed-won deals, you can't refine the model — you're scoring in the dark. Ghost closes this loop by maintaining attribution from the moment a lead is scored through outreach, opportunity creation, and deal closure. This means your scoring model improves over time, weighting the signals that actually predict revenue rather than the ones that merely look good on a dashboard.
The problem
Your lead scores don't connect to revenue outcomes. You can't tell whether high-scoring leads actually convert better than low-scoring ones, so you can't validate or improve your scoring criteria. The model is static and unproven.
How Ghost solves this
Ghost tracks scored leads through the entire funnel and feeds conversion data back into the scoring model. You can see exactly which engagement signals predict revenue, weight them accordingly, and continuously improve your scoring accuracy.
Ghost's attribution-fed scoring model improves lead-to-opportunity conversion by 35% within 90 days as it learns from actual revenue outcomes.