AI Image Prompt (click to expand)
Create a two-column comparison infographic. Left: Traditional Lead Scoring (red/warning style) showing activities: email opens, page visits, downloads → score. Right: Revenue-based Lead Scoring (green/gold) showing: ICP fit (company size, industry, role) + behavioral signals correlated to closed deals → score. Show the outcome difference: Traditional = „MQLs that don’t buy”, Revenue-based = „SQLs that convert”. Clean white background, B2B corporate style.
Replace this block with your image after generation. See implementation guide below.
The problem with traditional lead scoring
Typical scoring: +10 pts for email open, +20 for whitepaper download, +30 for pricing page visit. This measures marketing engagement — not purchase readiness. A B2B2C company downloading a PDF for research enters a sales rep’s pipeline and wastes their time.
Revenue-based lead scoring — the foundation
Instead of scoring activities, start by analyzing closed deals. Questions: What was the title of the person who signed? What industry? Which pages did they visit before contact? Which content did they download? These are the real ICP signals.
3-step revenue-based scoring implementation
1. Analyze last 50 closed deals — demographic and behavioral patterns. 2. Define ICP from data (not intuition). 3. Scoring model with weights based on correlation to closing — not to engagement.
Check if junk leads are your problem — Revenue Leak Self-Check