What is Lead Scoring?
Lead scoring is a systematic approach to ranking prospects by assigning numerical values to various attributes and behaviors. The resulting score helps sales teams prioritize their outreach efforts, focusing time and energy on leads most likely to convert.
Types of Lead Scoring
Demographic/Firmographic Scoring: Based on who the lead is.
- Job title and seniority level (+10 for VP, +5 for Manager)
- Company size and revenue (+8 for 100-500 employees)
- Industry alignment with ICP (+15 for target industry)
- Geographic location (+5 for target region)
Behavioral Scoring: Based on what the lead does.
- Website visits (+3 per visit, +10 for pricing page)
- Email engagement (+2 for open, +5 for reply)
- Content downloads (+8 for case study, +3 for blog post)
- Demo request (+25)
- Social media engagement (+4)
Negative Scoring: Deductions for disqualifying signals.
- Competitor employee (-50)
- Student email domain (-30)
- Unsubscribed from emails (-20)
- Job title mismatch (-15)
Lead Score Thresholds
Typical tier structure:
- Hot (80-100): Immediate outreach, high fit, strong engagement.
- Warm (50-79): Active nurturing, good fit, some engagement.
- Cool (25-49): Monitor, partial fit, low engagement.
- Cold (0-24): Deprioritize, poor fit or no engagement.
Building an Effective Scoring Model
- Analyze closed-won deals: What attributes and behaviors do your best customers share?
- Weight factors by impact: Not all signals are equal. A demo request is worth more than a blog visit.
- Include negative signals: Prevent wasted effort on leads that will never convert.
- Review and calibrate quarterly: Your scoring model should evolve with your business.
Common Mistakes
- Over-complicating the model: Start simple with 5-10 scoring criteria and refine over time.
- Ignoring negative signals: Without deductions, unqualified leads accumulate artificially high scores.
- Set-and-forget: Scoring models that aren't regularly calibrated against actual conversion data become useless.
How FlowStrata Scores Leads
FlowStrata uses a multi-dimensional scoring model that combines firmographic fit, behavioral engagement, intent data, and buying signal strength. Our system automatically recalculates scores as new data arrives, ensuring sales teams always see the most current prioritization. We calibrate scoring models monthly against actual conversion data to maintain accuracy.