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Extract structured property data from Zillow property detail pages, including price, address, bedrooms, bathrooms, square footage, property type, tax history, price history, coordinates, and market valuations.
The Zillow Property Scraper lets you extract structured property data from Zillow in bulk using property URLs. Just enter one or more Zillow property detail page links, and the scraper will automatically collect the key fields for each target property. It is designed for real estate research, price monitoring, market analysis, and property data archiving.
Compared with manually reviewing property pages one by one, this scraper makes it much faster to collect Zillow property detail data at scale and turn it into structured output for research, monitoring, and analysis.
| 🏠 Property ID (ZPID) | 📍 City, state, ZIP code, full address |
| 🛏️ Bedroom count | 🛁 Bathroom count |
| 💲 Current price, currency | 📅 Listing / sold date |
| 🏗️ Year built | 📐 Living area, lot size |
| 🏡 Property type | 🧭 Coordinates |
| 📈 Zestimate, Rent Zestimate | 🧾 Tax assessment, tax rate, tax history |
| 📝 Property description | 🕘 Price history, nearby properties, market insights |
The Zillow Product Scraper is designed to be simple to use, so you can start extracting data quickly even without prior scraping experience.
Enter the Zillow product URL you want to scrape. This version is best for cases where you already know the target property link and need a fast way to extract detail-page data, such as single-property monitoring, investment analysis, or competitor research.
When the run is complete, the collected Zillow data is organized under the Output tab as a structured dataset. For easier review, results are typically shown in a table-like view and structured fields. You can download the results or use them in downstream systems.
The scraper automatically visits Zillow property detail pages and converts unstructured page content into structured output. You only need to provide a property URL, and the scraper handles the collection process for you.
It can typically return ZPID, city, state, address, ZIP code, bedrooms, bathrooms, price, year built, property type, coordinates, square footage, valuations, tax fields, price history, property descriptions, and other related real estate data. Exact fields may vary depending on the property page.
Typical use cases include single-property monitoring, real estate investment analysis, price tracking, competitor property comparisons, internal property database building, and market intelligence collection.
The current tool description indicates that it uses a built-in proxy pool, IP rotation, CAPTCHA detection, redirect handling, and anti-bot mitigation to improve reliability in complex collection scenarios.
The current tool description states that CafeScraper uses HTTPS encryption for tool operations and follows fair use policies to support security and compliance requirements.
Yes. The current input setup supports batch submission, making it suitable for scraping multiple Zillow property detail page URLs in a single run.
Publicly accessible property data is commonly used for research, analytics, and business intelligence. That said, users should still comply with local privacy regulations and review the target website’s terms of service and compliance requirements.