Lead scoring

Lead scoring turns qualification from a judgment call into a repeatable process, which matters most when an event dumps several hundred contacts into your CRM at once. A typical model splits points between fit and behavior: fit points come from registration data (a VP at a target-industry company scores high; a student scores low), behavior points from what the person actually did (attended your demo, asked for pricing, spent ten minutes at the booth). Event interactions deserve heavier weighting than digital ones — showing up in person and having a conversation is a stronger signal than opening an email — and many teams get this wrong by running event leads through a scoring model built entirely for web behavior. Score thresholds should be set with sales, then tested: if high scorers aren't converting to opportunities, the model is measuring the wrong things. The honest nuance is that scoring is a prioritization tool, not a truth machine. A model is a set of guesses encoded in points, and it needs revisiting every couple of quarters against actual conversion data. The common mistake is building an elaborate model and never validating it — teams end up faithfully sorting leads by a formula nobody has checked in two years.