Lead scoring
Lead scoring assigns points to leads based on fit and behavior, such as role, company size, and engagement, so teams can prioritize the ones most likely to buy.
A scoring model adds or subtracts points for traits and actions. Fit points might reflect industry, company size, or job title; behavior points might reflect replies, clicks, or visits. The total helps rank who to contact first.
Scoring saves time when you have more leads than attention. The risk is a model built on guesses. Check it against your actual closed deals and adjust, because a score is only useful if it predicts real outcomes.
Keep the model simple enough to explain. Scores can come from fixed rules or from software that learns from past data, but in both cases a person should be able to see why a lead ranked where it did.
Common questions
How do you build a lead scoring model?
Start with traits your best customers share and behaviors that precede deals, assign points, then test the model against real outcomes and refine.
Does a high score guarantee a sale?
No. It is a prioritization aid, not a prediction you can rely on without checking.
Related terms
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