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 monthly

Variables 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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