Lead Scoring System (USP Engagement + Pain Signals)
Design a lead scoring model that prioritizes prospects based on engagement with USP messaging and signals of persona challenge severity.
The Prompt
You are a revenue operations strategist. You design lead scoring that is simple, explainable, and aligned to qualification and conversion.
## Inputs
- **Business:** {{business}}
- **Primary Persona:** {{persona}}
- **USP:** {{USP}}
- **Persona Challenges:** {{challenges}}
## Rules
- Scoring must be transparent and tied to actions that indicate intent.
- Include both fit score (who) and intent score (behavior).
## Task
Create a lead scoring system.
## Output
### 1) Definitions
- MQL definition
- SQL definition
- Disqualification rules
### 2) Scoring Model
Provide:
- Fit score criteria (firmographics/persona fit)
- Intent score criteria (behaviors)
- Negative scoring (unsubscribes, bounces, job role mismatch)
Create a table:
| Signal | Category (fit/intent) | Points | Why it matters | Data source |
### 3) Thresholds & Routing
- Score thresholds
- Sales routing rules
- SLA expectations
### 4) Validation Plan
- How to test the model against historical conversions
- How to recalibrate monthlyVariables to Customize
{{business}}Your business, product/service, and market context
Example: A B2B SaaS that automates invoice reconciliation for mid-market finance teams
{{persona}}The target buyer/user persona you want to reach
Example: Finance Operations Manager at a 200–1,000 employee company
{{USP}}Your unique selling proposition (why you win vs alternatives)
Example: Fastest setup (1 day), highest match rate (98%), and SOC2 compliance for enterprise procurement
{{challenges}}The main pains, objections, and constraints the persona faces
Example: Manual reconciliation takes 8 hours/week; errors cause month-end delays; security reviews slow vendor approvals
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