Focus Your Sales Team on the Right Leads
Data-driven lead scoring that surfaces high-intent buyers and stops your reps from wasting time on unqualified leads.
Lead Scoring Challenges
Junk MQLs
Sales rejects most MQLs because scoring rewards activity instead of buying intent.
No Fit Scoring
Every lead is treated the same regardless of company size, industry, or budget.
Stale Models
The scoring model was built two years ago and hasn't been recalibrated since.
Lead Scoring Services
Score smarter, convert faster
Scoring Model Design
Build fit + intent scoring models that align marketing and sales on what makes a quality lead.
- ICP fit scoring
- Behavioral scoring
- Negative scoring
- Threshold calibration
Lead Grading
Layer demographic and firmographic grading on top of scoring for complete lead qualification.
- Firmographic criteria
- Technographic signals
- Company size/revenue
- Industry match
Lifecycle Stages
Define clear stages from subscriber to customer with automated transitions.
- Stage definitions
- SLA agreements
- Handoff automation
- Recycling rules
Model Optimization
Continuously refine scoring based on closed-won/lost data and sales feedback.
- Conversion analysis
- Score decay
- A/B testing
- Quarterly review
Frequently Asked Questions
What's the difference between scoring and grading?
Scoring measures behavioral intent (what they do). Grading measures demographic/firmographic fit (who they are). The best models use both.
How often should we recalibrate scoring?
Quarterly at minimum. Recalibrate whenever you see MQL acceptance rates drop or win rates diverge from expectations.