AfrexAI Lead Hunter Pro

Turn your AI agent into a full B2B sales development machine. Discovery → Enrichment → Scoring → Outreach → CRM. Zero manual work.

---

Architecture

DEFINE ICP ──▶ DISCOVER ──▶ ENRICH ──▶ SCORE ──▶ SEGMENT ──▶ OUTREACH ──▶ CRM
    │              │            │          │          │            │          │
    ▼              ▼            ▼          ▼          ▼            ▼          ▼
 Persona      Multi-source  Email+Phone  ICP fit   Tier A/B/C  Sequences  Pipeline
 Builder      Web Research  Company Data  Intent    Campaigns   Templates  Tracking

---

Phase 1: Define Your Ideal Customer Profile (ICP)

Before hunting, know WHO you're hunting. Answer these:

Company-Level ICP

# Copy and customize this ICP template
company:
  industries: [SaaS, fintech, legal-tech, prop-tech]
  employee_range: [50, 500]        # sweet spot for AI adoption
  revenue_range: [$5M, $100M]      # can afford $120K+ contracts
  funding_stage: [Series A, Series B, Series C]
  tech_signals:                     # tools that indicate AI readiness
    positive: [Salesforce, HubSpot, Snowflake, AWS, Python]
    negative: [no-website, wordpress-only]
  geography: [US, UK, Canada, Australia]
  pain_signals:                     # problems they're likely facing
    - "manual data entry"
    - "compliance overhead"
    - "scaling operations"
    - "document processing"

Buyer Persona

persona:
  titles: [CEO, CTO, COO, VP Operations, Head of Innovation, Director of IT]
  seniority: [C-Suite, VP, Director]
  decision_authority: true          # can sign $50K+ without board approval
  linkedin_activity:                # signals they're actively looking
    - posts about AI/automation
    - comments on digital transformation content
    - recently changed roles (first 90 days = buying window)
  anti-signals:                     # skip these
    - "consultant" in title (not buyers)
    - company < 10 employees (no budget)
    - already has AI vendor (check for competitors in their stack)

Scoring Weights

scoring:
  icp_company_match: 30             # how well company matches
  icp_persona_match: 20             # right title + seniority
  intent_signals: 25                # actively looking for solutions
  engagement_recency: 15            # recent activity online
  timing_bonus: 10                  # new role, funding round, hiring
  
  thresholds:
    tier_a: 80                      # hot — outreach immediately
    tier_b: 60                      # warm — nurture sequence
    tier_c: 40                      # cool — add to newsletter
    disqualify: below 40            # don't waste time

---

Phase 2: Multi-Source Discovery

Source Priority Matrix

Source	Best For	How To Search	Data Quality	Cost
Web Search	Any industry	"[industry] companies" site:linkedin.com/company	High	Free
GitHub	Dev tools, tech companies	Search repos, org pages, contributor profiles	High	Free
Product Hunt	Startups, SaaS	Browse launches, upvoters (they're buyers too)	Medium	Free
Industry Lists	Targeted verticals	"Top 50 [industry] companies 2026", Clutch, G2	High	Free
Job Boards	Hiring = growing = buying	"AI" OR "automation" site:lever.co OR site:greenhouse.io	High	Free
Crunchbase	Funded startups	Recently funded companies in target verticals	High	Freemium
Conference Speakers	Active industry leaders	Speaker lists from industry events	Very High	Free
Podcast Guests	Thought leaders with budget	Search "[industry] podcast" transcripts	High	Free

Discovery Search Templates

Find companies by pain signal:

"[industry]" "manual process" OR "time-consuming" OR "looking for solutions" site:linkedin.com

Find companies by hiring signal (they're growing = they're buying):

"[company type]" "hiring" "AI" OR "automation" OR "data" site:linkedin.com/jobs

Find recently funded companies (flush with cash):

"[industry]" "raises" OR "Series A" OR "funding" OR "investment" 2026

Find companies using competitor tools (ripe for switching):

"[competitor tool]" "alternative" OR "switching from" OR "replaced"

Find decision makers directly:

"[title]" "[industry]" "[city/region]" site:linkedin.com/in

Discovery Workflow

FOR each search query:
  1. Run web_search with the query
  2. Extract company names + URLs from results
  3. Deduplicate against existing leads
  4. For each NEW company:
     a. Visit company website → extract: industry, size estimate, tech signals
     b. Search "[company name] CEO" OR "[company name] founder" → get decision maker
     c. Search "[company name] funding" → get financial signals
     d. Create lead record (see schema below)
  5. Rate limit: 2-3 second delay between searches

---

Phase 3: Enrichment Engine

For each discovered lead, enrich with verified data:

Company Enrichment Checklist

• Website — Load homepage, extract value prop, tech stack (check <meta> tags, JS frameworks)
• Employee Count — LinkedIn company page, Crunchbase, or website "About" page
• Revenue Estimate — Funding amount × 3-5x multiplier, or industry benchmarks
• Tech Stack — Check BuiltWith, Wappalyzer data, or job postings for tech mentions
• Recent News — Last 90 days: funding, launches, executive changes, partnerships
• Pain Indicators — Job postings mentioning problems you solve, blog posts about challenges
• Competitor Usage — Do they use a competitor? Which one? (Check G2 reviews, case studies)

Contact Enrichment Checklist

• Full Name — First + Last from LinkedIn or company page
• Title — Current role (verify it matches your buyer persona)
• Email Pattern — Determine company pattern: first@, first.last@, firstlast@, f.last@
• Email Verification — Test pattern with known format, check MX records
• LinkedIn URL — Direct profile link
• Recent Activity — What have they posted/shared in last 30 days?
• Mutual Connections — Anyone in your network connected to them?
• Content Interests — What topics do they engage with? (Use for personalization)

Email Pattern Detection

Common patterns (test in order of likelihood):
1. first.last@company.com     (most common, ~40%)
2. first@company.com          (startups, ~25%)
3. firstlast@company.com      (~15%)
4. flast@company.com           (~10%)
5. first_last@company.com     (~5%)
6. last.first@company.com     (~3%)
7. first.l@company.com        (~2%)

Verification approach:
- Check if company has public team page with email format
- Look for email in GitHub commits from company domain
- Check email format on Hunter.io or similar (if available)
- Search "[person name] email [company]" 
- Check their personal website/blog for contact

---

Phase 4: Lead Scoring Algorithm

Score each lead 0-100 using this rubric:

Company Score (0-30 points)

Signal	Points	How to Check
Industry matches ICP exactly	+10	Compare to ICP config
Employee count in sweet spot	+5	LinkedIn/website
Revenue in target range	+5	Crunchbase/estimate
Located in target geography	+3	Website/LinkedIn
Uses compatible tech stack	+4	Job posts, BuiltWith
No competitor currently	+3	Research, case studies

Persona Score (0-20 points)

Signal	Points	How to Check
Title matches buyer persona	+8	LinkedIn
C-Suite or VP level	+5	LinkedIn
Has decision authority	+4	Title + company size
Active on LinkedIn (posts monthly)	+3	LinkedIn activity

Intent Score (0-25 points)

Signal	Points	How to Check
Recently posted about relevant pain	+8	LinkedIn/Twitter
Company hiring for roles you'd replace	+7	Job boards
Attended relevant industry event	+5	Conference lists
Downloaded competitor content	+3	Hard to verify, skip if unknown
Searched for solution keywords	+2	Hard to verify, skip if unknown

Timing Score (0-15 points)

Signal	Points	How to Check
New in role (< 90 days)	+5	LinkedIn start date
Company just raised funding	+4	Crunchbase/news
End of quarter (budget flush)	+3	Calendar
Company growing fast (hiring surge)	+3	Job postings count

Engagement Score (0-10 points)

Signal	Points	How to Check
Opened previous email	+4	Email tracking
Visited your website	+3	Analytics
Connected on LinkedIn	+2	LinkedIn
Referred by someone	+1	CRM notes

---

Phase 5: Segmentation & Campaign Assignment

Tier A (Score 80-100) — HOT LEADS

Action: Immediate personalized outreach
Sequence: 5-touch hyper-personalized campaign
Timeline: Contact within 24 hours
Channel: Email → LinkedIn → Phone (if available)
Template: "CEO-to-CEO" or "Specific Pain" (see below)

Tier B (Score 60-79) — WARM LEADS

Action: Nurture sequence
Sequence: 7-touch value-first campaign  
Timeline: Start within 48 hours
Channel: Email → LinkedIn
Template: "Value Insight" or "Case Study" (see below)

Tier C (Score 40-59) — COOL LEADS

Action: Add to newsletter + long-term nurture
Sequence: Monthly value content
Timeline: Bi-weekly touchpoints
Channel: Email only
Template: "Industry Report" or "Educational" (see below)

---

Phase 6: Outreach Sequence Templates

Template 1: The Specific Pain (Tier A)

Email 1 — Day 0 (The Hook)

Subject: [specific pain point] at [Company]?

Hi [First Name],

Noticed [Company] is [specific observation — hiring for X role / posted about Y challenge / using Z tool].

That usually means [pain point they're likely feeling].

We built [solution] that [specific result with number]. [Client name] cut their [metric] by [X%] in [timeframe].

Worth a 15-min call to see if it fits [Company]?

[Your name]

Email 2 — Day 3 (The Proof)

Subject: Re: [original subject]

[First Name] — quick follow-up.

Here's exactly what we did for [similar company]: [1-sentence case study with specific numbers].

[Link to case study or calculator]

Happy to walk through how this maps to [Company].

[Your name]

Email 3 — Day 7 (The Angle)

Subject: [industry trend] + [Company]

[First Name],

[Industry trend or stat that's relevant]. Companies like [Company] are [what smart companies are doing about it].

We help [type of company] [specific outcome]. Takes about [timeframe] to see results.

Open to a quick chat this week?

[Your name]

Email 4 — Day 14 (The Breakup)

Subject: Should I close your file?

[First Name],

I've reached out a few times — totally understand if the timing isn't right.

If [pain point] becomes a priority, here's a [free resource] that might help: [link]

Either way, I'll stop filling your inbox. Just reply "yes" if you'd like to chat sometime.

[Your name]

Template 2: The Value-First (Tier B)

Email 1 — Lead with insight, not a pitch

Subject: [number] [industry] companies are doing [thing] wrong

Hi [First Name],

We analyzed [X] companies in [industry] and found that [surprising insight].

The ones getting it right are [what top performers do differently].

Put together a quick breakdown: [link to free resource/calculator]

Thought it'd be useful given what [Company] is building.

[Your name]

Template 3: The LinkedIn Warm-Up

Step 1: View their profile (creates notification) Step 2 (Day 2): Like/comment on their recent post (genuine, not generic) Step 3 (Day 4): Send connection request with note:

Hi [Name] — been following [Company]'s work in [space]. 
Particularly liked your take on [specific post topic]. 
Would love to connect.

Step 4 (Day 7, after accepted): Send value message (NOT a pitch):

[Name] — saw you mentioned [challenge] in your recent post. 
We put together [free resource] that addresses exactly that. 
Thought you might find it useful: [link]

---

Phase 7: CRM & Pipeline Management

Lead Record Schema

{
  "id": "lead-001",
  "created": "2026-02-13",
  "source": "web-search",
  
  "company": {
    "name": "Acme Corp",
    "website": "https://acme.com",
    "industry": "SaaS",
    "employees": 150,
    "revenue_est": "$20M",
    "funding": "Series B — $15M (2025)",
    "tech_stack": ["Salesforce", "AWS", "React"],
    "location": "San Francisco, CA"
  },
  
  "contact": {
    "first_name": "Jane",
    "last_name": "Smith",
    "title": "VP of Operations",
    "email": "jane.smith@acme.com",
    "email_verified": false,
    "linkedin": "https://linkedin.com/in/janesmith",
    "phone": null
  },
  
  "scoring": {
    "company_score": 25,
    "persona_score": 18,
    "intent_score": 15,
    "timing_score": 8,
    "engagement_score": 0,
    "total": 66,
    "tier": "B"
  },
  
  "enrichment": {
    "pain_signals": ["hiring 3 data analysts", "blog about manual reporting"],
    "recent_news": ["Raised Series B in Jan 2026"],
    "competitor_usage": "None detected",
    "content_interests": ["data automation", "operational efficiency"]
  },
  
  "outreach": {
    "status": "not_started",
    "sequence": "value-first",
    "emails_sent": 0,
    "last_contacted": null,
    "next_action": "2026-02-14",
    "replies": [],
    "notes": ""
  },
  
  "pipeline": {
    "stage": "prospect",
    "deal_value": null,
    "probability": 0,
    "next_step": "Initial outreach"
  }
}

Pipeline Stages

PROSPECT → CONTACTED → REPLIED → MEETING_BOOKED → QUALIFIED → PROPOSAL → NEGOTIATION → CLOSED_WON / CLOSED_LOST

Tracking Metrics

Track these weekly to optimize your machine:

• Discovery rate: leads found per search session
• Enrichment completeness: % of fields filled per lead
• Score distribution: what % are Tier A vs B vs C?
• Response rate: replies / emails sent (target: 5-15%)
• Meeting rate: meetings / replies (target: 30-50%)
• Conversion rate: deals / meetings (target: 20-30%)
• Pipeline velocity: days from discovery → closed deal

---

Phase 8: Automation & Scheduling

Daily Autopilot Routine

MORNING (agent runs autonomously):
  1. Run 3-5 discovery searches (rotate queries)
  2. Enrich any un-enriched leads from yesterday
  3. Score new leads
  4. Send Day-N emails for active sequences
  5. Check for replies → flag for human review
  6. Update pipeline stages
  7. Report: "Found X leads, sent Y emails, Z replies"

WEEKLY:
  1. Review Tier C leads — any moved to B/A?
  2. Clean dead leads (no response after full sequence)
  3. Analyze response rates by template — A/B test
  4. Refresh ICP based on closed deals
  5. Add new search queries based on wins

Agent Integration

# In your agent's heartbeat or cron:
1. Load ICP config
2. Run discovery for 1 search query
3. Enrich top 5 new leads
4. Score all unscored leads
5. Queue outreach for Tier A leads
6. Log results to daily brief

---

Output Formats

CSV Export

company,contact,title,email,linkedin,score,tier,industry,employees,pain_signal
Acme Corp,Jane Smith,VP Ops,jane@acme.com,linkedin.com/in/jane,66,B,SaaS,150,hiring analysts

Weekly Report Template

# Lead Hunter Weekly Report — Week of [DATE]

## Pipeline Summary
- Total leads in system: [N]
- New leads this week: [N]  
- Tier A: [N] | Tier B: [N] | Tier C: [N]

## Outreach Performance
- Emails sent: [N]
- Reply rate: [X%]
- Meetings booked: [N]
- Pipeline value added: $[X]

## Top Leads This Week
1. [Company] — [Contact] — Score: [X] — [Why they're hot]
2. [Company] — [Contact] — Score: [X] — [Why they're hot]
3. [Company] — [Contact] — Score: [X] — [Why they're hot]

## Insights
- Best performing search query: [query]
- Best performing email template: [template]
- Recommendation: [action to take]

---

Pro Tips

1. The 90-Day Window: New executives are 10x more likely to buy in their first 90 days. Prioritize "new role" signals.
2. Hiring = Buying: If a company is hiring for the role your product replaces, they have budget AND pain. These are your hottest leads.
3. Competitor's Customers: Search for reviews/complaints about competitors. Unhappy customers switch fastest.
4. Conference Lists: Speaker and attendee lists from industry events are gold. These people are actively engaged in the space.
5. The "Reply to Anything" Rule: Any reply (even "not interested") is valuable. It confirms the email works and the person exists. Log it.
6. Personalization > Volume: 20 hyper-personalized emails outperform 200 generic ones. Always reference something specific about the prospect.
7. Multi-Thread: Don't rely on one contact per company. Find 2-3 decision-makers and approach from different angles.
8. Timing Matters: Tuesday-Thursday, 8-10 AM local time gets the best open rates. Avoid Mondays and Fridays.

---

Built by AfrexAI — AI agents that actually sell.