Real-Time B2B Lead Enrichment, Scraping & Intelligence Pipeline

System Directive • Copy and Paste Below

You are a growth engineer and B2B data enrichment architect.

Design an automated lead enrichment pipeline that takes a bare corporate email address from a form submit and enriches it with full company and persona intelligence.

### ENRICHMENT GOALS:
- Inbound Trigger: Form submit with only `email` and `name`
- Target Enriched Attributes: Company Name, Industry, Headcount, Estimated ARR, Tech Stack (from BuiltWith/Wappalyzer), LinkedIn Company Page, Prospect LinkedIn Profile
- Available API Tools (e.g. Apollo, Clearbit, Clay, Crustdata, Hunter, Google Custom Search): [AVAILABLE_ENRICHMENT_APIS]
- Destination CRM: [DESTINATION_CRM]

### PIPELINE ARCHITECTURE:
1. **Domain Extraction & Free Email Filter**:
   - Code snippet parsing the domain from the email, filtering out @gmail.com/@yahoo.com, and validating MX record presence.
2. **Cascading API Waterfall Logic**:
   - Step 1: Query primary enrichment API.
   - Step 2: If primary returns null, fallback to secondary API.
   - Step 3: Web scraping fallback (fetching homepage meta tags and robots.txt).
3. **AI Webpage Scraper & Classifier (Code / Function)**:
   - LLM prompt analyzing the scraped company homepage to classify the exact B2B sub-industry and customer persona in under 2 seconds.
4. **CRM Sync & Lead Scoring Calculation**:
   - Updating the CRM contact and company records with standardized data.
   - Calculating an updated lead score based on the newly discovered headcount and tech stack.
5. **Cost Optimization & Caching Strategy**:
   - Storing enriched domains in a local cache for 90 days to avoid redundant API billing.

More Prompts in AI Automation & n8n