Property Intelligence Scraper
Automated property data pipeline pulling StreetEasy listings into a live Google Sheet on a 2-week cadence — built for a NYC real estate firm.
Overview
An automated property intelligence pipeline that scrapes StreetEasy listings and delivers structured data into a live Google Sheet on a 2-week cadence. Built for a NYC real estate firm that needed reliable, up-to-date market data without the manual research burden.
Problem
Real estate firms spend hours manually searching StreetEasy and copying listing data into spreadsheets. By the time the research is compiled, market conditions have shifted, and the process starts over again.
Approach
Built a Python scraping pipeline orchestrated through n8n that runs on a 2-week schedule. The scraper extracts key listing data (price, location, sqft, days on market), normalizes it, and pushes structured results directly into a shared Google Sheet via the Sheets API. Error handling and retry logic ensure reliable delivery.
Tech Stack
Results
Operational pipeline replacing 4 hours of manual research every 2 weeks. Delivering structured property data to the client's existing Google Sheets workflow with zero manual intervention.