Lead Scoring
A methodology for ranking prospects based on their likelihood to become customers using demographic and behavioral criteria.
Definition
Lead scoring assigns numerical values to leads based on various attributes and behaviors to determine their sales-readiness. Scoring models typically combine demographic fit (job title, company size, industry) with behavioral engagement (website visits, email opens, content downloads). Higher scores indicate leads that are more likely to convert and should be prioritized by sales.
Why It Matters
Not all leads are created equal. Lead scoring helps sales teams focus their limited time on the prospects most likely to buy, improving efficiency and conversion rates. It also creates alignment between marketing and sales on what constitutes a qualified lead.
Examples
- +10 points for viewing pricing page
- +5 points for downloading a case study
- +20 points for visiting 5+ pages in one session
How Bullseye Helps
Bullseye provides behavioral data that supercharges lead scoring. See exactly which pages a lead viewed, how many times they returned, and what content they engaged with. This behavioral intelligence makes scoring models far more accurate.
Related Terms
Buyer Intent Data
Behavioral signals that indicate a prospect's likelihood to purchase a product or service.
Marketing Qualified Lead (MQL)
A lead that has been determined by marketing to be more likely to become a customer based on engagement and fit criteria.
Sales Qualified Lead (SQL)
A prospect that has been vetted by the sales team and deemed ready for direct sales engagement.
Learn More
Related Use Cases
Lead Generation
Generate leads from your website without forms by identifying anonymous visitors.
Sales Intelligence
Real-time intelligence on website visitors for proactive sales outreach.
Account-Based Marketing (ABM)
Identify individuals from target accounts visiting your site for ABM programs.
Related Guides
Ready to identify your website visitors?
Start turning anonymous traffic into qualified leads today.