[GTM glossary](/glossary.md) Lead scoring Sales Development & Prospecting # Lead scoring In short Lead scoring is a system that assigns points to each lead based on who they are and what they do. A higher score signals a better fit or stronger interest, and helps decide who gets attention first. Scoring does not replace judgment. It orders the queue so reps spend their first hour on the leads most likely to convert. ## What goes into a score ### Fit points Based on traits that do not change quickly: industry, company size, region, job title, and tools used. ### Behavior points Based on actions: a demo request, pricing page visits, webinar attendance, or email replies. Strong actions earn more than light ones. ### Negative points Subtract for signals of poor fit, such as a personal email domain, a student title, or a competitor domain. Decay old activity so stale interest fades. --- ## How to build a simple score * **1. Review closed-won deals:** Find the traits and actions common to customers. * **2. Assign weights:** Give more points to traits that separate winners from losers. * **3. Set a threshold:** Pick the score at which a lead goes to sales. * **4. Test and adjust:** Compare scores with outcomes and revise each quarter. --- ## Example Say a team gives 20 points for a target industry, 15 for a director title or above, 30 for a demo request, 5 for a pricing page visit, and subtracts 25 for a personal email address. A lead reaching 60 goes to an SDR the same day. --- ## Common mistakes * **Mixing fit and interest in one number:** A perfect-fit lead with no interest looks the same as a poor-fit lead who clicked a lot. Keep them visible separately. * **Never validating:** Scores nobody checks against outcomes drift away from reality. * **Overcomplicating:** A dozen weighted rules you understand beat fifty you do not. * **Not telling sales what it means:** Reps ignore scores they do not trust. --- ## Lead scoring vs. lead scoring models Lead scoring is the practice. A scoring model is the specific design behind it: manual points, predictive machine learning, or a fit-and-intent grid. --- ## Lead scoring FAQs **What is lead scoring?** Lead scoring is a way of ranking leads by assigning points for fit traits and behavior, such as job title, company size, and demo requests. Sales uses the score to decide which leads to contact first. **How does lead scoring work?** You assign points to attributes and actions that correlate with becoming a customer, subtract points for poor-fit signals, and set a threshold. When a lead crosses it, the lead is routed to sales or an SDR for follow-up. **What is a good lead score?** There is no universal good score, because every team sets its own scale and threshold. A good score is one that reliably separates leads who convert from those who do not when checked against your closed deals. **How often should you update your lead scoring?** Review it at least quarterly. Compare scores with real outcomes such as meetings booked and deals won, then adjust weights and thresholds. Update sooner if your product, target market, or sales process changes. Share term --- ## More related phrases * [Inbound lead qualification](/glossary/inbound-lead-qualification.md) * [Intent leads](/glossary/intent-leads.md) * [Lead signals](/glossary/lead-signals.md) ## Similar phrases * [Predictive lead scoring](/glossary/predictive-lead-scoring.md) Predictive lead scoring uses a model trained on past deals to rank the leads in your database by how likely each one is to become a customer. * [AI lead scoring](/glossary/ai-lead-scoring.md) AI lead scoring uses machine learning to rank leads by how likely they are to buy, learning from past wins and losses instead of relying on manually assigned points. * [Fit score](/glossary/fit-score.md) A fit score is a number that rates how closely a company or contact matches your target customer, using static traits such as industry, size, and tech stack. * [Lead scoring models](/glossary/lead-scoring-models.md) Lead scoring models are the frameworks used to calculate lead scores, including manual point systems, predictive models, and fit and intent grids. * [Marketing qualified lead (MQL)](/glossary/marketing-qualified-lead.md) A marketing qualified lead (MQL) is a lead that marketing judges ready for sales follow-up based on fit with the target profile and engagement behavior.