AI-Powered Marketing Automation Platform
Engineered a comprehensive microservice architecture that leverages AI agents to automate complex marketing workflows. Includes a web crawler pipeline scanning 500+ websites daily for lead information, contributing to a 30% increase in qualified leads. The system boosted user engagement by 71.3% and features real-time reporting capabilities.
The Problem
The sales team spent hours manually researching potential leads across hundreds of websites. Marketing campaigns were generic and untargeted, resulting in low engagement rates. There was no automated pipeline connecting lead discovery to personalized outreach.
The Approach
Built three interconnected microservices: (1) A web crawler pipeline using Python and Scrapy that scans 500+ websites daily, extracting structured lead data with configurable selectors. (2) An AI agent layer using LangChain that analyzes lead profiles and generates personalized marketing content. (3) A workflow orchestrator built with FastAPI that sequences the pipeline — crawl, enrich, score, personalize, send — with real-time analytics dashboards for campaign performance.
Results
- 71.3% improvement in user engagement compared to manual campaigns
- 30% increase in qualified leads generated per quarter
- 500+ websites scanned daily with automated lead extraction
- Real-time analytics dashboards for campaign performance tracking
Lessons Learned
- AI-generated content needs human review guardrails — we added approval workflows for high-value leads
- Web scraping at scale requires robust error handling and rate limiting to avoid getting blocked
- The biggest ROI came from lead scoring, not content generation — prioritizing the right leads matters more than perfect copy