DFY GTM Systems

Lead Scoring Guide

By Abdul Sami, GTM Engineer · 6 min read · Last updated

Lead scoring = fit score (does this company match the ICP) + signal score (are they showing buying behavior now). Score each 0–50, add them, and route: 80+ gets personalized outreach, 50–79 gets sequences, below 50 waits. Scoring exists to spend human effort where it converts.

Fit score (0–50)

  • Industry match: 0/10/20.
  • Size in range: 0/10.
  • Geography servable: 0/10.
  • Tech/stack qualifier: 0/10.

Signal score (0–50)

  • Hiring relevant roles: +15.
  • Funding in last 6 months: +15.
  • Leadership/job change: +10.
  • Expansion or launch news: +10.
  • Visited site / engaged: +10.

Thresholds and routing

ScoreAction
80+Senior touch: trigger-based personalized email or call
50–79Standard sequence, segment copy
25–49Nurture; re-score on new signals
<25Drop from active lists

Common mistakes

  • Scoring on data you don't reliably have empty fields zero out real leads.
  • Too many factors 6–8 strong signals beat 30 weak ones.
  • Set-and-forget recalibrate quarterly against closed-won data.

FAQ

What is lead scoring?
A numeric model that ranks leads by fit (ICP match) and behavior (buying signals) so outreach effort goes to the leads most likely to convert now.
Where should scoring live?
As a computed column in Clay or your CRM, fed by enrichment and signal data not a spreadsheet someone updates by hand.
Predictive scoring vs rules-based?
Rules-based (points per attribute) wins until you have thousands of labeled outcomes. It is transparent, tunable, and doesn't need a data science project.
AS

Abdul Sami

GTM Engineer, DFY GTM Systems

7+ years building outbound systems for B2B companies across the US, UK, Australia, and DACH. Specializes in Clay workflows, cold email infrastructure, intent-based lead sourcing, and deliverability.

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