Lead Scoring
A method for assigning values to prospect attributes and behaviors to support prioritization or routing against an agreed outcome.
Well-governed scoring can focus sales effort, trigger appropriate nurturing and make qualification criteria explicit across marketing and sales.
A B2B model weights verified company fit and high-intent actions, applies inactivity decay and sends only leads above a validated threshold to sales review.
Scores can encode bias, reward noisy activity and drift as markets or tracking change. A score is not certainty and should not replace agreed qualification or human judgment.
Rules-based or predictive models combine fit, engagement, intent and negative signals. Scores require a defined target, reliable event data, thresholds, decay, versioning and validation against downstream conversion rather than arbitrary activity counts.
AI Governance, Data Engineering, Intelligent Automation
HubSpot — Lead Scoring Explained — https://blog.hubspot.com/marketing/lead-scoring-instructions; NIST — AI Risk Management Framework — https://www.nist.gov/itl/ai-risk-management-framework
