LLM Lead Conversion-Propensity Scoring for B2B Lead Prioritization
· 12 min read
The published literature on lead scoring converges on a couple of recurring findings. A B2B feature-importance analysis identified lead source and lead status as the most predictive conversion features (Frontiers in AI, 2025). And a supervised classifier trained on labelled outcomes tends to beat both rule-based heuristics and manual qualification. Yet many B2B teams deploying an LLM for lead prioritisation skip the classifier, skip the labelled outcomes, and instead ask the model to reason its way to a score from contact evidence. Is that defensible, or is it cargo-cult AI?