Lead Scoring

Lead scoring is a system that assigns numerical point values to each lead based on how closely they match your ideal customer profile (fit score) and how engaged they are with your brand (behavior score), producing a combined score that helps sales prioritize follow-up.

Without lead scoring, your SDRs are making subjective judgment calls about which leads to call first. With it, they have a data-driven ranking that ensures the hottest leads get attention immediately while lower-priority leads enter nurture sequences.

A typical scoring model has two components. Fit scoring evaluates static attributes: job title (+10 for VP of Sales, +2 for intern), company size (+15 for 200-500 employees if that matches your ICP), industry (+10 for SaaS, -5 for government). Behavior scoring evaluates actions: visited pricing page (+20), downloaded a case study (+10), opened an email (+2), requested a demo (+50).

For example, a lead who is a Director of Revenue Operations at a 300-person SaaS company (high fit) who visited your pricing page twice and attended a webinar (high engagement) might score 85 out of 100. That lead should be contacted within minutes, not days.

The biggest pitfall in lead scoring is set-it-and-forget-it. Your model needs regular calibration. Pull a report comparing lead scores to actual conversion rates. If leads scoring 80+ are converting at the same rate as leads scoring 50-60, your model isn’t differentiating effectively and needs adjustment.

Start simple. A basic model with 10-15 scoring criteria that you refine monthly will outperform a complex model with 100 rules that nobody maintains. Lead generation tools often include built-in scoring capabilities that adapt based on your historical conversion data.