A model that assigns numeric scores to leads based on fit (firmographic data) and engagement (behavioral signals) — used to prioritize sales outreach to the highest-probability buyers.
Lead Scoring combines two dimensions: fit (company size, industry, role — predicts whether the lead matches your ICP) and engagement (page views, content downloads, email clicks — predicts whether they're actively buying). Each signal carries a weight; total score crosses thresholds that trigger sales handoff or different marketing tracks. Modern stacks use ML to learn weights from historical conversion data instead of guessing them.
A B2B SaaS lead scoring model that gives +50 for VP+ title at >100-employee company and +5 per pricing page visit; sales gets notified at score 100.
Lead Scoring stops sales from chasing dead leads — focusing the team's attention on the 10-20% of leads most likely to close pays back many times over.
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