Automated lead generation from digital footprints with Decodo & Airtable

Description

Stop manually searching Google for sales leads. Start listening to the internet.

This advanced workflow automatically identifies, qualifies, and enriches high-value leads by searching for their digital footprints (i.e., specific technology use or public directories). It uses a robust Find/Create/Conditional Update database pattern to prevent duplicates and ensure you only spend credits on enriching incomplete records.

The workflow provides a fully persistent lead record, updating the same Airtable row as new data is found across multiple search steps.

✨ Key Features

Persistent Data Integrity: Uses a dedicated Loop Over Items structure to run the Find/Create/Update logic sequentially for every lead, guaranteeing no data is lost or duplicated.
Conditional Enrichment: A smart gate checks the Airtable record: if the high-value email field is empty, the workflow proceeds to the expensive scraping steps. If it is already complete, it skips the scrape.
Targeted Scraping: Executes precise Google Dorks (via Decodo) to find initial leads and then targets the specific Contact Us page for deep email extraction.
Database-as-a-State-Machine: Airtable acts as the single source of truth, logging the initial lead status and updating the same row across several enrichment phases.
Final Output: Delivers the fully enriched lead data (Domain, Primary Email, Contact Page URL) to a final notification channel.

⚙️ How it Works (The Find/Create/Update Loop)

Search & Filter: The workflow is manually triggered and uses the Config variables to execute a wide-scope Google Search via Decodo. The results are filtered into a clean array of unique domains.
Loop & Check: The Loop Over Items node starts. Inside, the Airtable Read node checks the database for the current lead's domain.
Create/Update:
If the lead is NEW, the workflow creates a record (Airtable: Create Lead).
If the lead EXISTS, the record is updated (Airtable: Update Lead).
Data Merger: The Data Merger: ID Finalizer node consolidates the workflow, ensuring the unique Airtable Record ID is passed to the next step, regardless of whether the lead was created or updated.
Conditional Enrichment: The If: Enrichment Needed? node checks the existing Primary Email status. If it's empty, the item proceeds to the deep scraping pipeline (Decodo: Email Search → Decodo: Scrape Contact Page).
Final Update: The final node updates the Airtable record with the high-quality email address found from the deep scrape.

📥 Decodo Node Installation

The Decodo node is used three times in this workflow for precision scraping and searching.

Find the Node: Click the + button in your n8n canvas.
Search: Search for the Decodo node and select it.
Credentials: When configuring the first Decodo node, use your API key.

🎁 Get a free Web Scraping API subscription here 👉🏻 https://visit.decodo.com/X4YBmy

🛠️ Setup Instructions

This template requires specific node configuration and Airtable fields.

Credentials: Obtain API keys for Decodo (using the coupon above) and Airtable.
Airtable Setup (Schema): Create an Airtable base with a 'Leads' table. It must include these fields for mapping:
Domain (Single Line Text - Primary Field)
Primary Email (Email)
Contact Page URL (URL)
Source URL (URL)
Lead Type (Single Select: Paid Ad Lead, Organic Lead)
Status (Single Select: New Lead, Updated, Enrichment Complete)
Global Configuration: Open the Config: Set Search Params node. Customize the following fields:
tech_footprint: e.g., "We use Klaviyo"
target_industry: e.g., site:promarketer.ca

➕ How to Adapt the Template

Change Database:* Replace the *Airtable* nodes with *Postgres, **Notion, or Google Sheets for logging, adapting the field mappings.
Final Notification:* Add a *Slack* or *Gmail** node to alert the sales team immediately upon successful enrichment.
Multi-Step Enrichment:** Integrate a service like Hunter.io or Clearbit to find key employee names and titles before the final database update.
Adjust Scoring:* Add an *If Node* after the deep scrape to set a *Lead Score based on whether a direct email (sales@) was found versus a general contact page link.
Add AI Lead Scoring:* Integrate a *Gemini* or *OpenAI** node after the deep scraping step to assign an "AI Score" (1-100) based on lead quality (e.g., domain authority, quality of the extracted email), before the final update.