Prompt Details
Model
Chat - (gpt-5.2)
Token size
477
Example input
[B2B / B2C / SaaS / Service / Ecommerce]: B2B SaaS
[Insert]: AI-powered workflow automation tool for small businesses
[Insert ]: Company size: 10–100 employees Roles: Founder, Operations Manager, Marketing Manager Geography: India, US, UK
[Short / Medium / Long ]: Medium (14–30 days)
[Prioritization / Sales Handoff / Nurturing / Segmentation]: Sales handoff + prioritization
Example output
1️⃣ Lead Scoring Objective Definition
What “Qualified” Means
A qualified lead:
Matches the ideal company size and role
Has shown clear intent (pricing page, demo, or trial interaction)
Has engaged multiple times within the last 14 days
When a Lead Moves to Sales
Lead score ≥ 70
At least 1 high-intent action completed
No major negative signals (unsubscribe, long inactivity)
When a Lead Stays in Nurture
Lead score between 30–69
Interest shown, but intent or urgency unclear
Still learning or comparing options
2️⃣ Scoring Criteria Breakdown
A. Demographic / Firmographic Fit (Max: 30 points)
Condition
Points
Company size 10–100
+15
Decision-maker role
+10
Target country
+5
Outside ICP
0
B. Behavioral Signals (Max: 25 points)
Behavior
Points
Email open
+2
Email click
+5
Website visit
+3
3+ visits in 7 days
+10
Webinar attendance
+15
C. Intent Actions (Max: 40 points)
Action
Points
Pricing page view
+15
Feature comparison page
+10
Demo request
+30
Free trial signup
+35
Case study download
+10
D. Negative Signals (Max: –40 points)
Signal
Points
14 days inactivity
–10
30 days inactivity
–25
Email unsubscribe
–40
Student / irrelevant role
–20
3️⃣ Score Thresholds & Lead Stages
Stage
Score Range
Status
Cold Lead
0–29
Awareness
Warm Lead
30–69
Consideration
Sales-Ready (SQL)
70–100
Action
Disqualified
≤ –10
Remove from funnel
Reset / Disqualification Rules
Unsubscribe → Immediate disqualification
60 days no activity → Score reset to 0
4️⃣ Automation Logic & Rules
Score Increase Rules
Real-time score update on:
Page visits
Email clicks
Form submissions
Score Decay (Time-Based)
–5 points every 7 days without engagement
Prevents old leads from staying “hot” forever
Triggered Actions
When score crosses 30 (Warm):
Add to “Education Nurture” email sequence
Send use-case & comparison content
When score crosses 70 (Sales-Ready):
Create sales task automatically
Assign to sales rep
Notify via Slack / CRM alert
Pause marketing emails
5️⃣ Sales & Marketing Alignment
Sales Team Actions
Cold: No action
Warm: Light check-in or LinkedIn connect
Sales-Ready:
Contact within 24 hours
Personal demo or consultation
Marketing Team Actions
Warm leads → Problem + solution education
Sales-ready → Proof, urgency, ROI messaging
Feedback Loop
Sales marks leads as:
“Good fit”
“Too early”
“Not relevant”
Marketing adjusts scoring weights monthly based on outcomes
6️⃣ Monitoring & Optimization Guidance
Metrics to Track
Lead → SQL conversion rate
Sales response time
Demo-to-close ratio
Average score at close
When to Adjust Scoring
Too many low-quality SQLs → Increase intent weight
Sales saying “leads too cold” → Raise sales-ready threshold
Leads converting without high scores → Review missing signals
Signs the Model Is Off
Sales ignoring CRM alerts
High scores but low close rates
Long delays between score jump and contact
Safe Optimization Tips
Adjust weights, not structure first
Change thresholds in small steps (±5–10 points)
Review performance every 30 days
By purchasing this prompt, you agree to our terms of service
GPT-5.2
Many teams waste time following up with leads who are not ready to convert.
This prompt helps you design a clear, automated lead scoring logic that prioritizes high-intent leads based on behavior, engagement, and fit—so sales and marketing stay aligned.
✨ What You Receive:
📊 Clear lead scoring framework
🧠 Behavior and intent-based scoring logic
🔄 Automation-ready rules and thresholds
🎯 Sales-readiness indicators
📌 Practical implementation guidance
👉 Designed for marketers and sales teams u
...more
Added over 1 month ago
