This project serves as a technical showcase for building highly customized, scheduled data extraction and transformation pipelines using n8n. The primary focus was on achieving reliable scheduling, complex data parsing, and multi-system integration.

The client required granular, structured data on specific property listings and market trends available on Zillow.

Manual Inefficiency: The existing process involved a person manually searching, navigating pages, and extracting property attributes, which was inherently slow and impossible to scale beyond a few dozen listings.

The Data Bottleneck: The data captured manually was inconsistent, often stored in spreadsheets that lacked validation, making it unusable for direct integration into their analytical models and investment tools.

The Goal: The core objective was to create a system that could reliably query hundreds of properties and transform the raw HTML content into clean, JSON-structured data ready for database ingestion.

I engineered a robust, server-side workflow using n8n to automate the end-to-end data lifecycle from Apify, from collection to delivery.

Scheduled Trigger: The workflow was configured with a flexible schedule (e.g., set to run every 4 hours) for maximum update cadence.

Request Handling: Custom HTTP requests were structured to navigate Zillow's publicly available pages.

Advanced Data Parsing: This was the core of the project. I utilized n8n's Function Node and Custom Code to implement advanced techniques for parsing complex HTML/DOM structures. This included:

Transformation & Schema Validation: The parsed data was rigorously cleaned, validated against a target schema, and formatted into clean JSON objects, ready for any downstream system.

Data Output: The final, structured data was configured to integrate with the client's preferred endpoint (e.g., a PostgreSQL database or Airtable).

Disclaimer: I must explicitly state that Zillow’s Terms of Use generally prohibit "automated queries (including screen and database scraping, spiders, robots, crawlers, bypassing “captcha” or similar precautions, or any other automated activity with the purpose of obtaining information from the Services)" on their website.

Parsing Precision: Achieved an extraction success rate of over 98% for the core data fields across a test set of 500+ properties, demonstrating the robustness of the parsing logic.

Data Latency: The system successfully reduced the potential data latency from days to mere hours. A full extraction run, which took a person 4 hours manually, was completed by the n8n workflow in 12 minutes.

Scalability: The architecture was proven to handle a tenfold increase in the number of monitored properties without needing major structural changes, showcasing true scalability potential.

This case study demonstrates my ability to engineer complex, customized data workflows—even in technically challenging environments. My expertise lies in designing resilient automation that delivers quantifiable results:

Deep Technical Proficiency: I build robust data parsing, transformation, and integration logic using n8n and custom code.

Let's transform your inefficient processes into reliable, hands-off automation. I specialize in workflows that connect CRMs, streamline internal reporting, manage complex data imports, and integrate disparate cloud services—all within legal and ethical boundaries.

Contact me on Contra today to get started!!