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.

Pythonn8nGoogle Sheets APIWeb Scraping

Problem

Real estate firms spend hours every two weeks manually searching StreetEasy, copying listing data into spreadsheets, and formatting it for analysis. By the time the research is compiled, market conditions have shifted and the process starts again — a recurring time sink with no leverage.

Solution

A Python pipeline orchestrated through n8n that scrapes StreetEasy listings on a 2-week cadence. It extracts key data — price, location, square footage, days on market — normalizes it, and pushes the structured results directly into the client's existing Google Sheet. The client opens the same spreadsheet they've always used; it's automatically populated with current market data.

Results

4 hours of manual research eliminated every 2 weeks
Zero manual intervention for data delivery
2-week automated cadence
Delivered into client's existing workflow

Tech Stack

Pythonn8nGoogle Sheets APIBeautifulSoup

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