AI-Powered Lead Qualification & Scoring
Use this prompt to
Build an agentic workflow that ingests inbound leads from a CRM export, scores them against your ICP, drafts personalized outreach sequences, and flags high-priority leads for immediate follow-up.
Pro tip
Connect this to n8n or Make.com to run automatically when new leads hit your CRM. Add a human-in-the-loop approval step before outreach is sent.
Prompt Variants by Model
Claude
Claude 4.x
FRESH APR 2026
You are a sales operations analyst. I am going to provide a CSV export of inbound leads from our CRM. Your job is to build a lead scoring and outreach system.
<ideal_customer_profile>
Industry:...You are a sales operations analyst. I am going to provide a CSV export of inbound leads from our CRM. Your job is to build a lead scoring and outreach system.
<ideal_customer_profile>
Industry: [TARGET_INDUSTRIES]
Company size: [EMPLOYEE_RANGE]
Role/Title: [DECISION_MAKER_TITLES]
Budget indicator: [REVENUE_RANGE or SIGNALS]
Geography: [REGIONS]
</ideal_customer_profile>
<scoring_rubric>
- ICP match (0-30 points): industry, size, role alignment
- Engagement signals (0-25 points): website visits, content downloads, email opens
- Timing signals (0-20 points): recent funding, hiring surge, tech stack changes
- Fit quality (0-25 points): use case alignment, pain point match
</scoring_rubric>
For each lead:
1. Calculate a score (0-100) with reasoning
2. Classify as Hot (75+), Warm (50-74), or Cold (<50)
3. For Hot leads: draft a personalized 3-touch outreach sequence (email 1: value hook, email 2: social proof, email 3: direct ask)
4. For Warm leads: draft a nurture email
5. Flag any leads that need human review (incomplete data, conflicting signals)
Process the attached CSV and output results as a structured table plus the drafted emails.
Notes: Claude handles large CSV analysis natively. Use Artifacts or Projects for persistent ICP storage. The XML-tagged scoring rubric gives Claude clear guardrails.
ChatGPT
GPT-5
FRESH APR 2026
You are a B2B sales ops expert. I'm uploading a CSV of our inbound leads. Score and qualify each one against our ICP, then draft outreach.
**Our Ideal Customer Profile:**
-...You are a B2B sales ops expert. I'm uploading a CSV of our inbound leads. Score and qualify each one against our ICP, then draft outreach.
**Our Ideal Customer Profile:**
- Industries: [TARGET_INDUSTRIES]
- Company Size: [EMPLOYEE_RANGE]
- Decision Maker: [TITLES]
- Budget Range: [REVENUE_RANGE]
- Region: [REGIONS]
**Scoring Model (100 points total):**
- ICP Match: 30 pts (industry, size, role)
- Engagement: 25 pts (site visits, downloads, opens)
- Timing: 20 pts (funding, hiring, tech changes)
- Fit: 25 pts (use case, pain point alignment)
**For each lead, output:**
1. Score (0-100) + short reasoning
2. Tier: Hot (75+) / Warm (50-74) / Cold (<50)
3. Hot leads → 3-email outreach sequence (value hook → social proof → direct CTA)
4. Warm leads → 1 nurture email
5. Flag leads with missing data for human review
Use Code Interpreter to process the CSV. Output a summary table + full email drafts.
Notes: Upload the CSV directly — Code Interpreter processes it natively. Use Custom Instructions to store your ICP permanently.
Gemini
Gemini 3 Pro
FRESH APR 2026
I have a CSV export of inbound leads I need scored and qualified. Please help me build a lead scoring system.
**My ideal customer:**
-...I have a CSV export of inbound leads I need scored and qualified. Please help me build a lead scoring system.
**My ideal customer:**
- Industries: [TARGET_INDUSTRIES]
- Company size: [EMPLOYEE_RANGE]
- Decision makers: [TITLES]
- Budget signals: [REVENUE_RANGE]
- Geography: [REGIONS]
**Score each lead out of 100:**
- ICP alignment (30 pts)
- Engagement level (25 pts)
- Timing signals (20 pts)
- Use case fit (25 pts)
**Then:**
- Classify as Hot (75+), Warm (50-74), or Cold (under 50)
- Write a 3-email outreach sequence for Hot leads
- Write a single nurture email for Warm leads
- Flag any leads with incomplete data
I will paste/upload the lead data. Please output a scored table and all email drafts.
Notes: Gemini handles file uploads well. For live CRM data, pair with Google Sheets integration for automated scoring refreshes.
Copilot
Copilot (Microsoft 365)
FRESH APR 2026
I need to score and qualify a list of sales leads from my CRM.
**Who we sell to (ideal customer):**
- Industries: [TARGET_INDUSTRIES]
- Company...I need to score and qualify a list of sales leads from my CRM.
**Who we sell to (ideal customer):**
- Industries: [TARGET_INDUSTRIES]
- Company size: [EMPLOYEE_RANGE]
- Who we talk to: [TITLES]
- Budget range: [REVENUE_RANGE]
- Where: [REGIONS]
**How to score (out of 100):**
- Does the lead match our ideal customer? (30 points)
- How engaged are they with our content? (25 points)
- Are there buying signals like recent funding or hiring? (20 points)
- Do they have a use case we solve well? (25 points)
For each lead, give me: a score, a Hot/Warm/Cold label, and if they are Hot write a 3-email outreach sequence. For Warm leads, write one nurture email. Flag anything with missing info.
I will paste the lead data below.
Notes: Copilot in Microsoft 365 can pull CRM data from Dynamics 365 natively. For standalone use, paste lead data directly.
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