Skill: 1kalin/afrexai-lead-hunter (version 1.0.0)

--- name: afrexai-lead-hunter description: "Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously." tags: [leads, sales, b2b, prospecting, enrichment, outreach, pipeline, crm, cold-email, icp] author: AfrexAI version: 1.0.0 license: MIT --- # 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 ```yaml # 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 ```yaml 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 ```yaml 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. [REDACTED_SECRET] (most common, ~40%) 2. [REDACTED_SECRET] (startups, ~25%) 3. [REDACTED_SECRET] (~15%) 4. [REDACTED_SECRET] (~10%) 5. [REDACTED_SECRET] (~5%) 6. [REDACTED_SECRET] (~3%) 7. [REDACTED_SECRET] (~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 ```json { "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": "[REDACTED_SECRET]", "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 ```csv company,contact,title,email,linkedin,score,tier,industry,employees,pain_signal Acme Corp,Jane Smith,VP Ops,[REDACTED_SECRET],linkedin.com/in/jane,66,B,SaaS,150,hiring analysts ``` ### Weekly Report Template ```markdown # 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](https://afrexai-cto.github.io/context-packs/) — AI agents that actually sell.*


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