ai-marketing-skills/sales-pipeline

🎯 AI Sales Pipeline

Turn anonymous website visitors into qualified pipeline in under 60 seconds.

A complete AI-powered sales pipeline automation suite: from website visitor identification through intent scoring, suppression, campaign routing, dead deal resurrection, trigger-based prospecting, and self-learning ICP optimization.

These tools were built in production at Single Grain, processing thousands of visitors and deals weekly. Now open-sourced for any B2B company to use.

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Architecture

                         ┌─────────────────────────────────────────┐
                         │           YOUR WEBSITE(S)               │
                         └──────────────┬──────────────────────────┘
                                        │ RB2B pixel fires
                                        ▼
                    ┌───────────────────────────────────────┐
                    │      rb2b_webhook_ingest.py           │
                    │  Intent Scoring + ICP Classification  │
                    │  (pricing=90, blog=30, services=65)   │
                    └──────────────┬────────────────────────┘
                                   │ High-intent visitors
                                   ▼
              ┌────────────────────────────────────────────────┐
              │        rb2b_suppression_pipeline.py            │
              │  5-Layer Check:                                │
              │  CRM → Outbound → Stripe → Analytics → Block  │
              │  + Company-level dedup (1 per domain/week)     │
              └──────────────┬─────────────────────────────────┘
                             │ Clean leads only
                             ▼
              ┌────────────────────────────────────────────────┐
              │        rb2b_instantly_router.py                │
              │  Agency Detection + Source Site Routing        │
              │  → Routes to correct Instantly campaign        │
              │  → Auto-activates paused campaigns             │
              └────────────────────────────────────────────────┘

  ┌────────────────────┐  ┌────────────────────┐  ┌─────────────────────┐
  │  deal_resurrector  │  │ trigger_prospector  │  │ icp_learning_       │
  │       .py          │  │       .py           │  │    analyzer.py      │
  │                    │  │                     │  │                     │
  │ 3 intelligence     │  │ Monitors:           │  │ Reads approve/      │
  │ layers on dead     │  │ • New CMO hires     │  │ reject decisions    │
  │ deals:             │  │ • Job postings      │  │                     │
  │ 1. Time decay      │  │ • Funding rounds    │  │ Outputs:            │
  │    scoring         │  │ • Agency searches   │  │ • Industry targets  │
  │ 2. POC expansion   │  │                     │  │ • Size sweet spots  │
  │ 3. Follow the      │  │ Scores, enriches,   │  │ • Title patterns    │
  │    champion        │  │ drafts outreach     │  │ • Revenue ranges    │
  └────────────────────┘  └─────────────────────┘  └─────────────────────┘
           │                        │                         │
           └────────────────────────┼─────────────────────────┘
                                    ▼
                        ┌───────────────────────┐
                        │   Your CRM / Outbound │
                        │   (HubSpot, Instantly) │
                        └───────────────────────┘

---

Tools

1. 🌐 RB2B Webhook Ingest (rb2b_webhook_ingest.py)

Receives RB2B visitor identification webhooks, scores intent based on pages visited, and classifies ICP fit.

What it does:

• Scores every page visit against configurable intent patterns (pricing page = 90, blog = 30)
• Checks ICP fit by title seniority + company size
• Outputs structured signals with priority levels (high/medium/low)
• Runs as HTTP server or processes stdin/batch files

# Run as webhook server
python3 rb2b_webhook_ingest.py --serve --port 4100

# Test with sample data
echo '{"email":"cmo@acme.com","job_title":"CMO","company":"Acme Inc","company_size":500,"pages_visited":["https://yoursite.com/pricing"]}' | python3 rb2b_webhook_ingest.py --dry-run

2. 🛡️ Suppression Pipeline (rb2b_suppression_pipeline.py)

5-layer suppression that prevents embarrassing outreach to existing customers, active leads, or competitors.

Layers:

1. Personal Email Filter — Skip gmail.com, yahoo.com, etc.
2. CRM Check — Already in HubSpot? Don't cold email them.
3. Outbound Platform — Already in an Instantly campaign (last 90 days)?
4. Payment Provider — Paying Stripe customer? Definitely don't cold email.
5. Blocklist — Competitor domains + manual blocks
6. Company Dedup — Only 1 contact per company domain per 7-day window

# Check a single email
python3 rb2b_suppression_pipeline.py --email john@acme.com --company "Acme Inc"

# Output:
# 📋 Suppression check for: john@acme.com
# ──────────────────────────────────────────────────
#   ✅ Personal Email Filter: business email
#   ✅ CRM Check: not in CRM
#   ✅ Outbound Platform: not in outbound platform
#   ✅ Payment Provider: not a paying customer
#   ✅ Blocklist: not blocklisted
#   ✅ Company Dedup: no company dedup conflict
# ──────────────────────────────────────────────────
#   ✅ CLEAR — eligible for enrollment

3. 🔀 Instantly Router (rb2b_instantly_router.py)

The orchestrator: combines intent scoring + suppression + agency classification to route leads to the right Instantly campaign automatically.

What it does:

• Scores visitor intent
• Runs full suppression pipeline
• Classifies agency vs. non-agency visitors (2+ signal threshold)
• Detects source site (if you have multiple properties)
• Routes to the correct campaign and auto-enrolls via Instantly API
• Auto-activates paused campaigns when leads are ready

# Run as webhook server (production mode)
python3 rb2b_instantly_router.py --serve --port 4100

# Dry run test
echo '{"email":"vp@techco.com","job_title":"VP Marketing","company":"TechCo","industry":"SaaS","company_size":"200","pages_visited":["https://yoursite.com/pricing","https://yoursite.com/case-studies"]}' | python3 rb2b_instantly_router.py --dry-run

4. 🔥 Deal Resurrector (deal_resurrector.py)

Three intelligence layers on your closed-lost deals. Finds the best revival opportunities using a composite scoring formula.

Layer 1 — Time Decay Scoring (0-100):

• Time component (35 pts): 60-90 days = sweet spot, decays over time
• Value component (30 pts): Normalized deal value
• Reason component (20 pts): "Timing" deals score higher than "bad fit"
• Trigger component (15 pts): Bonus if recent email opens or site visits

Layer 2 — POC Expansion:

• Verifies if your contact is still at the company
• Finds replacement decision-makers when contacts leave

Layer 3 — Follow the Champion:

• Tracks departed contacts to their new companies
• If they moved to an ICP-fit company, generates outreach for the new org

# Find top 10 revival opportunities (dry run)
python3 deal_resurrector.py --top 10 --dry-run

# Full run with champion tracking
python3 deal_resurrector.py --top 5 --include-champion

# Exclude a company from future runs
python3 deal_resurrector.py --add-exclusion "Already Won Corp"

5. 🔍 Trigger Prospector (trigger_prospector.py)

Scans the web for buying signals: new marketing leadership hires, job postings, funding rounds, and active agency searches.

Signal Categories:

Signal	What It Means	Score Weight
New CMO/VP hire	Budget reallocation window	35 pts
Job posting	Growth mode, team building	25 pts
Funding round	Capital to deploy	30 pts
Agency search	Active evaluation	40 pts

Each prospect gets a composite score (0-100) plus enrichment: estimated company size, industry, suggested services, outreach channel recommendation, and a ready-to-send email draft.

# Scan last 7 days for signals
python3 trigger_prospector.py --days 7 --top 15

# Wider scan with lower threshold
python3 trigger_prospector.py --days 30 --top 25 --min-score 40

6. 📊 ICP Learning Analyzer (icp_learning_analyzer.py)

Your ICP should evolve from data, not guesswork. This tool reads your prospect approve/reject history and outputs recommended filter changes.

What it analyzes:

• Industry patterns (which convert vs. get rejected)
• Company size sweet spots (10th-90th percentile of approvals)
• Title/seniority patterns
• Revenue ranges
• Per-source approval rates (cold vs. trigger vs. warm vs. revival)

# Run analysis
python3 icp_learning_analyzer.py

# With custom config
python3 icp_learning_analyzer.py --config data/icp-config.json

# Example output:
# 📊 ICP Learning Analyzer Results
#    Total prospects analyzed: 847
#    ────────────────────────────────────────
#    cold      : ready                (n=312, approval=23%)
#              → Target: SaaS, Fintech, E-commerce
#              → Exclude: Crypto/Web3
#              → Employees: 50-500
#    trigger   : ready                (n=156, approval=41%)
#              → Target: SaaS, Healthcare
#              → Employees: 100-1000
#    warm      : ready                (n=289, approval=67%)
#    revival   : insufficient_data    (n=12, min_required=30)

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Quick Start

1. Clone and install

git clone https://github.com/nichochar/ai-marketing-skills.git
cd ai-marketing-skills/sales-pipeline
pip install -r requirements.txt

2. Configure environment

cp .env.example .env
# Edit .env with your API keys

3. Set up campaign config (for RB2B Router)

cp data/campaigns.json.example data/campaigns.json
# Add your Instantly campaign UUIDs

4. Test with dry runs

# Test suppression pipeline
python3 rb2b_suppression_pipeline.py --email test@example.com

# Test intent scoring
echo '{"email":"test@example.com","pages_visited":["https://yoursite.com/pricing"]}' \
  | python3 rb2b_webhook_ingest.py --dry-run

# Test deal resurrector
python3 deal_resurrector.py --top 5 --dry-run

# Test trigger prospector
python3 trigger_prospector.py --days 7 --top 10

5. Deploy webhook server

# Start the full pipeline as a webhook endpoint
python3 rb2b_instantly_router.py --serve --port 4100

# Point your RB2B webhook (or Zapier/Make) at:
# POST http://your-server:4100/

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Customization

Intent Scoring

Edit PAGE_INTENT_SCORES in rb2b_webhook_ingest.py to match your site's URL structure:

PAGE_INTENT_SCORES = {
    "pricing": 90,      # Your pricing page path
    "demo": 85,         # Demo request page
    "case-study": 70,   # Social proof pages
    "blog": 30,         # Low-intent content
    # Add your own patterns...
}

Agency Detection

Modify AGENCY_KEYWORDS_COMPANY and AGENCY_INDUSTRIES in rb2b_instantly_router.py for your market.

Loss Reason Scoring

Customize LOSS_REASON_BONUS in deal_resurrector.py based on which loss reasons actually convert when revisited.

Trigger Queries

Edit SEARCH_QUERIES in trigger_prospector.py to target your specific market signals.

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Integrations

Tool	Required	Used By
RB2B	For visitor ID	Webhook Ingest, Router
Instantly	For cold email	Router, Suppression
HubSpot	For CRM	Deal Resurrector, Suppression
Brave Search	For web signals	Trigger Prospector
PostgreSQL	For ICP learning	ICP Analyzer
Stripe	Optional	Suppression (customer check)

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File Structure

sales-pipeline/
├── README.md                          # This file
├── SKILL.md                           # Claude Code skill definition
├── requirements.txt                   # Python dependencies
├── .env.example                       # Environment variable template
├── rb2b_webhook_ingest.py            # Webhook server + intent scoring
├── rb2b_suppression_pipeline.py      # 5-layer suppression checks
├── rb2b_instantly_router.py          # Full pipeline orchestrator
├── deal_resurrector.py               # Dead deal revival engine
├── trigger_prospector.py             # Web signal prospecting
├── icp_learning_analyzer.py          # Self-learning ICP optimization
└── data/
    ├── campaigns.json.example         # Instantly campaign config template
    └── icp-config.example.json        # ICP analyzer config template

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How It Works Together

1. RB2B identifies anonymous website visitors with name, email, company, title
2. Webhook Ingest scores their intent based on which pages they viewed
3. Suppression Pipeline checks 5 layers to avoid emailing existing contacts
4. Router classifies agency vs. non-agency, picks the right campaign, enrolls
5. Meanwhile, Deal Resurrector mines your CRM for revival opportunities
6. Trigger Prospector scans the web for companies showing buying signals
7. ICP Analyzer learns from your approve/reject decisions and tightens targeting

The result: a self-improving pipeline that gets better the more you use it.

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Built by Single Grain · Open-sourced as part of AI Marketing Skills

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Built by Single Grain

We help companies grow with AI-powered marketing. These are the tools we use internally.

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