Lead Scoring Models

Detailed scoring templates, example models by business type, and calibration guidance.

Explicit Scoring Template (Fit)

Company Attributes

Attribute	Criteria	Points
Company size	1-10 employees	+5
	11-50 employees	+10
	51-200 employees	+15
	201-1000 employees	+20
	1000+ employees	+15 (unless enterprise-focused, then +25)
Industry	Primary target industry	+20
	Secondary target industry	+10
	Non-target industry	0
Revenue	Under $1M	+5
	$1M-$10M	+10
	$10M-$100M	+15
	$100M+	+20
Geography	Primary market	+10
	Secondary market	+5
	Non-target market	0

Contact Attributes

Attribute	Criteria	Points
Job title	C-suite (CEO, CTO, CMO)	+25
	VP level	+20
	Director level	+15
	Manager level	+10
	Individual contributor	+5
Department	Primary buying department	+15
	Adjacent department	+5
	Unrelated department	0
Seniority	Decision maker	+20
	Influencer	+10
	End user	+5

Technology Attributes

Attribute	Criteria	Points
Tech stack	Uses complementary tool	+15
	Uses competitor	+10 (they understand the category)
	Uses tool you replace	+20
Tech maturity	Modern stack (cloud, SaaS-forward)	+10
	Legacy stack	+5

Implicit Scoring Template (Engagement)

High-Intent Signals

Signal	Points	Decay
Demo request	+30	None
Pricing page visit	+20	-5 per week
Free trial signup	+25	None
Contact sales form	+30	None
Case study page (2+)	+15	-5 per 2 weeks
Comparison page visit	+15	-5 per week
ROI calculator used	+20	-5 per 2 weeks

Medium-Intent Signals

Signal	Points	Decay
Webinar registration	+10	-5 per month
Webinar attendance	+15	-5 per month
Whitepaper download	+10	-5 per month
Blog visit (3+ in a week)	+10	-5 per 2 weeks
Email click	+5 per click	-2 per month
Email open (3+)	+5	-2 per month
Social media engagement	+5	-2 per month

Low-Intent Signals

Signal	Points	Decay
Single blog visit	+2	-2 per month
Newsletter open	+2	-1 per month
Single email open	+1	-1 per month
Visited homepage only	+1	-1 per week

Product Usage Signals (PLG)

Signal	Points	Decay
Created account	+15	None
Completed onboarding	+20	None
Used core feature (3+ times)	+25	-5 per month inactive
Invited team member	+25	None
Hit usage limit	+20	-10 per month
Exported data	+10	-5 per month
Connected integration	+15	None
Daily active for 5+ days	+20	-10 per 2 weeks inactive

Negative Scoring Signals

Signal	Points	Notes
Competitor email domain	-50	Auto-flag for review
Student email (.edu)	-30	May still be valid in some cases
Personal email (gmail, yahoo)	-10	Less relevant for B2B; adjust for SMB
Unsubscribe from emails	-20	Reduce engagement score
Bounce (hard)	-50	Remove from scoring
Spam complaint	-100	Remove from all sequences
Job title: Student/Intern	-25	Low buying authority
Job title: Consultant	-10	May be evaluating for client
No website visit in 90 days	-15	Score decay
Invalid phone number	-10	Data quality signal
Careers page visitor only	-30	Likely a job seeker

Example Scoring Models

Model 1: PLG SaaS (ACV $500-$5K)

Weight: 30% fit / 70% engagement (heavily favor product usage)

Fit criteria:

Company size 10-500: +15
Target industry: +10
Manager+ role: +10
Uses complementary tool: +10

Engagement criteria:

Created free account: +15
Completed onboarding: +20
Used core feature 3+ times: +25
Invited team member: +25
Hit usage limit: +20
Pricing page visit: +15

Negative:

Personal email: -10
No login in 14 days: -15
Competitor domain: -50

MQL threshold: 60 points Recalibration: Monthly (fast feedback loop with high volume)

Model 2: Enterprise Sales-Led (ACV $50K+)

Weight: 60% fit / 40% engagement (fit is critical at this ACV)

Fit criteria:

Company size 500+: +20
Revenue $50M+: +15
Target industry: +15
VP+ title: +20
Decision maker confirmed: +15
Uses competitor: +10

Engagement criteria:

Demo request: +30
Multiple stakeholders engaged: +20
Attended executive webinar: +15
Downloaded ROI guide: +10
Visited pricing page 2+: +15

Negative:

Company too small (<100): -30
Individual contributor only: -15
Competitor domain: -50

MQL threshold: 75 points Recalibration: Quarterly (longer sales cycles, smaller sample size)

Model 3: Mid-Market Hybrid (ACV $5K-$25K)

Weight: 50% fit / 50% engagement (balanced approach)

Fit criteria:

Company size 50-1000: +15
Target industry: +10
Manager-VP title: +15
Target geography: +10
Uses complementary tool: +10

Engagement criteria:

Demo request or trial signup: +25
Pricing page visit: +15
Case study download: +10
Webinar attendance: +10
Email engagement (3+ clicks): +10
Blog visits (5+ pages): +10

Negative:

Personal email: -10
No engagement in 30 days: -10
Competitor domain: -50
Student/intern title: -25

MQL threshold: 65 points Recalibration: Quarterly

Threshold Calibration

Setting the Initial Threshold

Pull closed-won data from the last 6-12 months
Retroactively score each deal using your new model
Find the natural breakpoint — what score separated wins from losses?
Set threshold just below where 80% of closed-won deals would have scored
Validate against closed-lost — if many closed-lost score above threshold, tighten criteria

Calibration Cadence

Business Type	Recalibration Frequency	Why
PLG / High volume	Monthly	Fast feedback loop, lots of data
Mid-market	Quarterly	Moderate cycle length
Enterprise	Quarterly to semi-annually	Long cycles, small sample size

Calibration Steps

Pull MQL-to-closed data for the calibration period
Compare scored MQLs vs. actual outcomes:
- High score + closed-won = correctly scored
- High score + closed-lost = possible false positive (tighten)
- Low score + closed-won = possible false negative (loosen)
Adjust weights based on which attributes actually correlated with wins
Adjust threshold if MQL volume is too high (raise) or too low (lower)
Document changes and communicate to sales team

Warning Signs Your Model Needs Recalibration

MQL-to-SQL acceptance rate drops below 30%
Sales consistently rejects MQLs as "not ready"
High-scoring leads don't convert; low-scoring leads do
MQL volume spikes without corresponding revenue
New product/market changes since last calibration