Lead scoring model
A two-axis fit and engagement model you can build in any CRM.
LEAD SCORING MODEL: {{company}} Reviewed: {{date}}
FIT SCORE (who they are), maximum {{100}}
Industry in ICP: +{{20}}
Employee range in ICP: +{{20}}
Title in target buyer list: +{{25}}
Seniority manager or above: +{{10}}
Location in served market: +{{15}}
Uses a tool that signals fit: +{{10}}
Personal email domain: {{-20}}
Competitor or student: {{-50}}
ENGAGEMENT SCORE (what they did), capped at {{100}}
Requested a demo or a call: +{{50}}
Visited pricing page: +{{20}}
Attended a webinar or event: +{{15}}
Downloaded a guide: +{{10}}
Opened or clicked three or more emails in 30 days: +{{10}}
Replied to outbound: +{{25}}
No activity for 60 days: {{-20}}
ROUTING
Fit {{60}}+ and engagement {{50}}+: MQL. Call within {{time}}.
Fit {{60}}+ and engagement under {{50}}: nurture, plus outbound if the account is a target.
Fit under {{60}}: marketing nurture only. No SDR call.
Demo request from any fit {{40}}+: call within {{time}} regardless of engagement.
SQL: an MQL becomes an SQL when the SDR confirms {{framework}} at {{score}} or above on a call.When to use it
When inbound volume is high enough that SDRs cannot call every lead within an hour, or when marketing and sales disagree about what an MQL is.
Why it works
Separating fit from engagement stops a student who downloads five guides from outranking a buyer at a target account who visited the pricing page once. Negative points keep the queue clean.
Variations
- For outbound only teams, drop engagement scoring and use fit plus trigger events to rank the call list.
- For product-led growth, add product usage points such as active users invited or a key feature used.
Common mistakes
- Scoring only engagement, so the busiest content readers rise to the top.
- Never reviewing the weights against which scored leads actually closed.
- Setting the MQL threshold so low that SDRs ignore the queue.