Lead scoring assigns each lead a numeric rank from 0 to 100 so reps can see at a glance who is most likely to convert.
Two signal types
Scoring blends two layers: fit (does this lead match our ICP?) and engagement (are they actively interested?). Both are configurable per pipeline.
Configure fit signals
- Go to
/app/crm→ Pipelines → your pipeline → Settings → Scoring. - Define the ideal customer profile: industry, company size, role, country. Each match adds points.
- Set negative points for disqualifiers (e.g., individual consumers if you only sell B2B).
Configure engagement signals
Behavioral signals auto-add points: page views on your CMS, webform submissions, email opens, demo bookings via the AI scheduler, replies to outbound. Decay reduces engagement points if the lead goes cold for >30 days.
Use the score
The CRM list view sorts by score by default. Dashboard widgets show top-10 hot leads. Automations can trigger when a lead crosses a threshold (e.g., score > 70 → assign to a senior rep + send a personalized email).
Tips
- Start simple: 3-4 fit rules + 2-3 engagement signals. Add complexity later.
- Calibrate against your closed-won history: pull the closed deals from the last 90 days, check what their scores would have been.
- The ML scoring (Lead Scoring v2) trains automatically once you have ≥50 closed-won and ≥50 closed-lost leads.