Lead Scoring

Lead scoring assigns numerical values to each lead based on attributes and behaviors that indicate how likely they are to become a customer. Scores help sales teams prioritize who to reach out to first.

There are two main dimensions of lead scoring:

• Demographic/firmographic scoring — based on who the lead is: job title, seniority, company size, industry, revenue, and location
• Behavioral scoring — based on what the lead does: website visits, content downloads, email opens, demo requests, and product usage

Modern lead scoring increasingly uses AI and enriched data to automate what was traditionally a manual, rules-based process. By enriching leads with additional data points (like tech stack, funding stage, or hiring signals), teams can build more predictive scoring models.

Without lead scoring, reps waste time on low-fit prospects while high-value leads go cold. Teams with effective scoring models see faster sales cycles and higher win rates because they focus effort where it matters most.