Lead scoring is the process of assigning numerical values to leads based on their likelihood to become customers. Done right, it helps sales teams prioritize their time on prospects with the highest conversion potential, dramatically improving efficiency and results.
The Two Dimensions of Lead Scoring
Effective lead scoring evaluates prospects on two dimensions:
Fit Score
How well does this company match your Ideal Customer Profile? Consider industry, size, technology, and business model.
Intent Score
How engaged is this prospect? Track website visits, content downloads, email opens, and other behavioral signals.
Building Your Scoring Model
Step 1: Analyze Closed-Won Deals
Identify patterns in your best customers. What firmographic traits do they share? What behaviors predicted their conversion?
Step 2: Define Scoring Criteria
Assign point values to each attribute. Weight them based on correlation with conversion—title matches ICP +10 points, pricing page visit +15 points.
Step 3: Set Thresholds
Define what score makes a Marketing Qualified Lead (MQL) versus Sales Qualified Lead (SQL). Start conservative and adjust based on feedback.
Step 4: Implement Negative Scoring
Subtract points for disqualifying factors: wrong industry, too small, competitor domain, unsubscribed from emails.
Step 5: Continuously Refine
Review scoring effectiveness monthly. If high-scoring leads aren't converting, adjust the model based on real data.
AI-Powered Scoring
Leads10 automatically scores prospects based on their match to your ICP. Each generated lead includes a fit score that helps you prioritize outreach to the companies most likely to become customers.