Automated Lead Research, Signal Tracking & Change Detection

Built a fully automated lead research and signal-tracking system that continuously enriches CRM records, detects meaningful changes, and delivers instant alerts plus weekly summaries. The workflow replaces manual lead research with AI-driven monitoring, comparison logic, and automated reporting.

Project Overview

This project involved building an end-to-end automated lead intelligence pipeline that performs weekly lead research, signal tracking, and change detection without any manual work.

The system continuously monitors leads stored in Airtable, enriches them with fresh external data, compares new signals against historical records, and proactively notifies stakeholders when important updates occur.

The result is a hands-off lead monitoring system that keeps sales and growth teams informed in real time.

The Solution

I designed a multi-source lead research and signal-tracking automation using n8n as the orchestration layer.

The system combines AI-powered research, web scraping, data comparison, and automated reporting into a single pipeline.

Data Sources & Research Tools Integrated
AI & Research Engines
Perplexity – contextual research and summaries
Tavily – targeted web intelligence retrieval

Web Scraping & Crawling

Firecrawl – structured website content extraction
LinkedIn scraping – profile and activity signal collection
CRM & Storage

Airtable
Historical lead records
Change-tracking fields

Before / After Comparison
BEFORE: Manual Lead Research

Manual Google searches
Manual LinkedIn checks
Inconsistent research quality
Missed news and signals
Outdated CRM data
Time-heavy weekly reviews

Reactive and unreliable.

AFTER: Automated Lead Intelligence Pipeline

Continuous data enrichment
AI-driven research aggregation
Automatic change detection
Instant alerts on hot signals
Always-up-to-date CRM
Clean weekly summaries

Proactive, scalable, and reliable.