AfrexAI Lead Hunter Pro

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

Source Priority Matrix

SourceBest ForHow To SearchData QualityCostWeb SearchAny industry"[industry] companies" site:linkedin.com/companyHighFreeGitHubDev tools, tech companiesSearch repos, org pages, contributor profilesHighFreeProduct HuntStartups, SaaSBrowse launches, upvoters (they're buyers too)MediumFreeIndustry ListsTargeted verticals"Top 50 [industry] companies 2026", Clutch, G2HighFreeJob BoardsHiring = growing = buying"AI" OR "automation" site:lever.co OR site:greenhouse.ioHighFreeCrunchbaseFunded startupsRecently funded companies in target verticalsHighFreemiumConference SpeakersActive industry leadersSpeaker lists from industry eventsVery HighFreePodcast GuestsThought leaders with budgetSearch "[industry] podcast" transcriptsHighFree

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)

SignalPointsHow to CheckIndustry matches ICP exactly+10Compare to ICP configEmployee count in sweet spot+5LinkedIn/websiteRevenue in target range+5Crunchbase/estimateLocated in target geography+3Website/LinkedInUses compatible tech stack+4Job posts, BuiltWithNo competitor currently+3Research, case studies

Persona Score (0-20 points)

SignalPointsHow to CheckTitle matches buyer persona+8LinkedInC-Suite or VP level+5LinkedInHas decision authority+4Title + company sizeActive on LinkedIn (posts monthly)+3LinkedIn activity

Intent Score (0-25 points)

SignalPointsHow to CheckRecently posted about relevant pain+8LinkedIn/TwitterCompany hiring for roles you'd replace+7Job boardsAttended relevant industry event+5Conference listsDownloaded competitor content+3Hard to verify, skip if unknownSearched for solution keywords+2Hard to verify, skip if unknown

Timing Score (0-15 points)

SignalPointsHow to CheckNew in role (< 90 days)+5LinkedIn start dateCompany just raised funding+4Crunchbase/newsEnd of quarter (budget flush)+3CalendarCompany growing fast (hiring surge)+3Job postings count

Engagement Score (0-10 points)

SignalPointsHow to CheckOpened previous email+4Email trackingVisited your website+3AnalyticsConnected on LinkedIn+2LinkedInReferred by someone+1CRM notes

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)

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]

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

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

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

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