AI lead scoring
AI scores leads by likelihood to convert using behavioral, firmographic, and intent signals, so reps work the best leads first. It lifts conversion 30–75% and cuts unqualified leads reaching sales by around 56%.
The signals that predict conversion
AI weighs behavior (what the lead did), firmographics (who they are), and intent (buying signals) far more consistently than human intuition, ranking leads so effort flows to the highest-probability opportunities.
Human reps over-weight recency and gut feel; AI weighs the full signal set the same way every time. The payoff is not just higher conversion but reclaimed time, about 3.2 hours a day per rep no longer spent chasing dead leads. Reinvesting that time into high-scoring leads is what turns scoring from a dashboard metric into revenue.
Frequently asked questions.
Does lead scoring require a lot of data?
It works better with more history, but modern scoring can start from behavioral and firmographic signals you already collect. The bigger requirement is acting on the scores, routing and prioritizing by them, not ignoring them.