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 (obtained with the 80% discount coupon). 🎁 Exclusive Deal for n8n Users To run this workflow, you require a robust scraping provider. We have secured a massive discount for Decodo users: Get 80% OFF the 23k Advanced Scraping API plan. Coupon Code: ATTAN8N Sign Up Here: Claim 80% Discount on Decodo 🛠️ 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.