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OUTBOUNDGROWTH SIGNAL

Growth Signal Icebreaker

Growth signal detected. Personalized icebreaker written. Zero manual steps.

49 nodes4 workflowsn8n · Pronto · Airtable · Claude · LaGrowthMachine▶ watch walkthrough

The Problem

Generic cold emails get ignored. Truly personalized ones take 10+ minutes each to write. AI SDR tools burn LLM budget on undeliverable emails and template copy. This system detects companies actively growing, finds matching decision-makers, generates a unique icebreaker per lead using 3 layers of context, and enrolls them in outbound. Every Monday. Zero manual steps.

Stack

⚙️
n8n
Orchestrates all 4 decoupled async workflows
🔍
Pronto
Hiring + growth signal detection, lead search, and bulk enrichment
📋
Airtable
Shared state store — companies, contacts, settings, and mid-flight inspection
🧠
Claude
3-layer icebreaker generation: lead context + company signal + knowledge base
🚀
LaGrowthMachine
Outbound sequence enrollment via API

Walkthrough

How It Works

The execution path

01Signal Detected
→
02Company Enriched
→
03Lead Qualified
→
04Icebreaker Sent
Execution flow
WF1 fires Monday 9am— hiring + growth signals
Pronto detects signal companies— async
WF2 receives companies → enriches → saves to Airtable
Submit lead search with airtable_company_id
WF3 receives leads → filters ICP → saves to Airtable
Bulk enrich: airtable_lead_id + airtable_company_id in custom field
WF4 receives enriched contact → Pronto echoes IDs back
Merge 3 layers → Claude writes icebreaker → LGM enrolls
The hardest engineering problem: WF4 receives an enriched contact from Pronto — but Pronto has no concept of your internal IDs. The data thread solves this by passing airtable_company_id and airtable_lead_id through Pronto's custom field. Pronto echoes them back. WF4 always finds the exact right records.
WF1 — Signal Trigger (Monday 9:00am)

Reads targeting config from Airtable Settings and fires TWO parallel async calls to Pronto simultaneously — hiring signal and growth signal. Both are fire-and-forget.

  • ·Read targeting config from Airtable Settings
  • ·Fire async: companies posting sales/revenue roles (hiring signal)
  • ·Fire async: companies growing headcount above threshold (growth signal)
  • → Both calls deliver results to WF2 via webhook
WF2 — Company Reception + Enrichment (webhook)

Receives company batches and processes one at a time with a 30-second rate limit. Saves each to Airtable, gets the record ID, then submits an async lead search — passing the Airtable ID forward.

  • ·Parse and normalize company payload
  • ·Loop one company at a time (30s rate limit)
  • ·Enrich via Pronto: LinkedIn URL, headcount, industry
  • ·Save to Airtable Companies → receive record ID
  • ·Look up persona UUID from Airtable Personas table
  • ·Submit async lead search scoped to company domain + persona
  • → Pass airtable_company_id with the search request
WF3 — Lead Reception + Enrichment (webhook)

Filters leads by ICP title before spending enrichment credits. The critical move: passes both airtable_lead_id and airtable_company_id through Pronto's custom field so WF4 can find the right records.

  • ·Parse leads array
  • ·Filter: CTO, Chief Technology Officer, VP Engineering only
  • ·Save qualified leads to Airtable Contacts (linked to company)
  • ·Aggregate into bulk enrichment request
  • ·Pass airtable_lead_id + airtable_company_id via Pronto custom field
  • → Pronto echoes custom field back in enrichment webhook
WF4 — Icebreaker Generation + Enrollment (webhook)

Merges 3 data layers — lead context, company signal, and product knowledge base — before Claude writes. Email is a hard gate: if no deliverable email, Claude never fires. Zero wasted LLM spend.

  • ·Receive enriched contact + custom IDs from Pronto
  • ·Fetch lead details from Airtable using airtable_lead_id
  • ·Fetch company details from Airtable using airtable_company_id
  • ·Fetch knowledge base + LGM audience ID from Airtable Settings
  • ·Merge: lead context + company signal + knowledge base
  • ·Claude writes icebreaker (1–2 sentences, never starts with "I" or lead name)
  • ·Update Airtable: icebreaker saved, Enrichment Status = "Enriched"
  • ·POST to LaGrowthMachine: enroll in outbound sequence
  • ·Update Airtable: LGM Status = "Enrolled", LGM Enrolled At = today

Key Design Decisions

🧵
The Data Thread
airtable_company_id travels through Pronto's custom field across all 4 workflows. WF4 finds the exact right records every time with no shared state.
🎯
3-Layer AI Context
Lead + company signal + knowledge base, all merged before Claude writes. Every icebreaker is unique. None are templates.
🚪
Email as Hard Gate
Claude only fires when a deliverable email exists. Zero wasted LLM spend on unverified contacts.
🔍
Airtable as Inspection Layer
Every company, lead, icebreaker, and status is visible mid-flight. Any stage can be re-triggered independently.

By The Numbers

49
Nodes
4
Workflows
0
Wasted LLM calls
3
Context layers per icebreaker
← back to all systemsmatthew batterson · gtm engineer