菜单
Implements a lead scoring model that evaluates prospects based on demographic fit, firmographic data, behavioral engagement, and intent signals. Assigns numerical scores to prioritize sales outreach and route leads to the right team. Continuously refines scores based on conversion outcomes.
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基于 SOC 职业分类
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| name | lead-scoring |
| displayName | Lead Scoring |
| tagline | Score and prioritize leads based on engagement, firmographics, and behavioral signals. |
| description | Implements a lead scoring model that evaluates prospects based on demographic fit, firmographic data, behavioral engagement, and intent signals. Assigns numerical scores to prioritize sales outreach and route leads to the right team. Continuously refines scores based on conversion outcomes. |
| department | ["Marketing","Sales"] |
| use_cases | ["Lead Qualification","Sales Prioritization","Marketing Automation"] |
| tools_required | ["HubSpot MCP"] |
| agents_compatible | ["Claude / Claude Code","Cursor","Windsurf","ChatGPT","Any MCP-compatible agent"] |
| author | Webrix |
| verified | true |
| updatedAt | "2026-05-08T00:00:00.000Z" |
| version | 1.0.0 |
| exampleInput | Create a lead scoring model for our B2B SaaS product. ICP: 50-500 employee tech companies in North America. |
| exampleOutput | Lead Scoring Model — B2B SaaS SCORING CRITERIA (0-100) Firmographic (40 pts max) Company size 50-500: +15 Tech industry: +10 North America: +10 Revenue >$5M: +5 Behavioral (40 pts max) Visited pricing page: +10 Downloaded whitepaper: +8 Attended webinar: +8 Multiple site visits: +7 Opened 3+ emails: +7 Engagement (20 pts max) Requested demo: +15 Replied to outreach: +5 THRESHOLDS Hot (80-100): Route to SDR immediately Warm (50-79): Add to nurture sequence Cold (0-49): Continue marketing touches |
Score and prioritize leads based on engagement, firmographics, and behavioral signals.
Integrations: HubSpot
Establish firmographic and demographic criteria for ideal customers.
Define engagement actions and their point values.
Set score ranges for hot, warm, and cold lead categories.
Validate the model against historical conversion data.
Deliver:
