What Is Lead Scoring?
Lead scoring is the practice of assigning points to leads based on their fit (firmographics) and engagement (behavior) to rank how sales-ready they are. A good scoring model focuses reps on the leads most likely to convert and triggers the MQL handoff at the right threshold.
Key takeaways
- Lead scoring ranks leads by fit + engagement so reps work the best ones first.
- Models can be rule-based (manual points) or predictive (AI).
- Calibrate the threshold against leads that historically converted.
Fit vs engagement
Two dimensions drive a score. Fit asks “should we want them?” — industry, size, role matching your ICP. Engagement asks “do they want us?” — page views, email opens, demo requests. A high score needs both: a perfect-fit company that's actively engaging.
Manual vs predictive
Manual scoring uses points you assign to attributes and behaviors. Predictive scoring uses a model trained on your conversion history to estimate likelihood automatically. Predictive adapts on its own; manual is transparent and easy to start with.
Frequently asked questions
What is lead scoring?
Assigning points to leads based on fit and engagement to rank how sales-ready they are, so reps prioritize the most promising ones.
How does lead scoring work?
You define which attributes and behaviors add or subtract points, sum them into a score, and set a threshold (often the MQL line) for handoff.
What's the difference between manual and predictive lead scoring?
Manual scoring uses rules you set; predictive scoring uses a model trained on historical conversions to estimate likelihood automatically.
Related service: Build lead scoring in HubSpot