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How to Scrape Zillow Data for Free?

Q: Is Zillow API still active?

No, Zillow API is no longer active. Businesses have to transition to the Bridge API for real estate data access.

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Can You Scrape Data From Zillow?

Zillow is an online marketplace where people buy, sell, and rent homes. Its website has data on over 135 million properties in the US and Canada.

Due to how rich Zillow is in real estate information, people scrape data on the platform. However, Zillow can be challenging and expensive.

This article teaches you how to scrape Zillow data for free, along with the challenges that come with the process.

🔑 Key Takeaways

Zillow's terms strictly forbid scraping its data without prior approval.

You can scrape Zillow using Python or web scraping tools like Octoparse.

Scraping Zillow aids lead generation, real estate analysis, competitor tracking, and property valuation.

Expect anti-scraping measures, dynamic content, potential IP blocking, and data complexity while scraping Zillow data.

Always adhere to Zillow's rules and policies to avoid legal issues and access restrictions.

Can You Scrape Data From Zillow?

Scraping data from Zillow is against their terms and conditions and is not allowed. According to Zillow's Terms of Use:

"You are prohibited from displaying any other Zillow's Companies' data without our prior written approval."

“By using the Services, you agree not to:

[...] Conduct automated queries (including screen and database scraping, spiders, robots, crawlers, bypassing "captcha" or similar, or any other automated activity with the purpose of obtaining information from the Services) on the Services."

To sum up the site’s terms, Zillow says you cannot show data from their website without permission. Using tools or apps to gather information from Zillow is also restricted.

The good thing is there are some exceptions to those terms. For instance, extracting data from Zillow’s website is not prohibited as long as it is for personal and non-commercial purposes. You can also use Zillow’s data if the website allows you to use it.

If you’re scraping for personal reasons or have already asked permission from the site directly, continue reading to know how you can start with your Zillow scraping project.

8 Steps to Scrape Zillow Data for Free Using Python

Python is considered the best programming language for scraping. It can extract information from any web page. Python also provides various libraries that are easy to learn and use. These reasons and more are why Python is one of the most effective ways to scrape data from Zillow.

Here are the steps to build a free Zillow scraper using Python:

1. Install the Required Libraries

Open your terminal or command prompt. Type the following commands one at a time to install the requests, BeautifulSoup, and Pandas libraries:

pip install requests

pip install beautifulSoup

pip install pandas

2. Create a Python File

Make a Python file to write scripts in your code editor.

3. Import the Libraries

Import the libraries you installed in your script file by running the commands below:

import requests

from bs4 import BeautifulSoup

import pandas as pd

4. Send Requests to the URL

Use the request library to send the Zillow URL and get the HTML content of the page.

url = "insert-the-url-here"

response = requests.get(url)

5. Parse the HTML Content

Use the BeautifulSoup library to parse the HTML content and scrape the desired data.

For example, you wanted to scrape the address and price of listings on a page. You can use the following commands:

soup = BeautifulSoup(response.content, “html.parser”)

addresses = [address.text for address in soup.select('address')]

prices = [price.text.split() [0] for price in soup.select(“div.list-card-card-price”)]

6. Gather the Extracted Data

Gather the extracted data into the pandas data frame.

Data = {"address": addresses, “price”: prices}

df = pd.DataFrame(data)

7. Save the File

Save the file and go to the folder where it is located in your terminal or command prompt.

8. Run the Script

Run the Python script in your command prompt or terminal.

✅ Pro Tip

Avoid overloading Zillow servers with multiple requests in a short time. Implement delays between every request so your IP address will not be blocked while scraping.

Scrape Zillow Data for Free Using Scraping Tools

Besides Python, you can utilize third-party tools to gather data from Zillow. The process varies depending on the scraping tool you’re using. Below are simple steps for using the Octoparse Zillow scraper:

1. Download and Install Octoparse

Download and install the Octoparse app on your computer.

2. Search the Zillow Template

Launch the installed tool. In the search bar, type “Zillow.” Click the Zillow template in the search result.

Octoparse dashboard

3. Input the URL

Click Try it and enter the URL of the Zillow listing you want to scrape.

Initiating scraping in Octoparse

4. Start Scraping

Click the Start button and scrape the data.

5. Export Data

Once the tool is finished scraping, export the data according to your desired file format.

Exporting data in Octoparse

The photo below shows how the extracted data will look when exported to Excel:

Sample of Octoparse’s extracted data

👍 Helpful Article

Other than real estate data, you can also scrape photos and profiles on social media sites using scraping tools. Check out this article to learn how you can extract data from Instagram.

Zillow Scraping Use Cases

People scrape Zillow data to learn more about the listings on the site. Here are use cases showing how beneficial Zillow web scraping is:

Lead Generation – Scraping Zillow data helps gather details on potential customers interested in real estate.
Competitor Analysis – Real estate agents and developers often keep tabs on competitors to monitor property pricing and listing strategies. Having a Zillow data scraper makes it easy to keep an eye on rival real estate companies.
Real Estate Market Analysis – Data extracted from Zillow is valuable to real estate investors and homebuyers. Scraping real estate data from Zillow allows investors and buyers to understand more about property listings, prices, and the market.

💡Did You Know?

An American family spends around $5,500 on housing alone in 2023, which means more than 33% of the household’s income goes to rent or mortgages.

The average spending of families in the US on housing only shows how real estate pricing and market value are continuously increasing.

Research and Property Valuation – People who buy or sell properties can estimate a property’s worth by scraping Zillow’s data on recently sold properties and listings.

Challenges of Scraping Data from Zillow

You learned how valuable scraping Zillow data is in the previous section. Despite the usefulness and how seamless the scraping process may seem, you may encounter challenges while doing so.

Here are some obstacles when scraping Zillow data:

	Anti-Scraping Measures Zillow uses various methods to spot and stop web scraping. The site can block IP addresses, stop automated tools, and add CAPTCHAs to interfere with your scraping.
	Dynamic Content Zillow might load details dynamically using code. This means the content may not appear on the webpage immediately, making data collection harder.
	IP Blocking Zillow can block your IP address or site access if you scrape excessively.
	Data Complexit Zillow shares loads of data on each property listed on the website. Organizing data according to every property can be complex.

Besides the points mentioned above, the biggest challenge in scraping Zillow is the probability of facing legal issues. You have to be careful when scraping the website. When it deems that you did not follow its terms, Zillow itself may file a lawsuit for your action.

✅ Pro Tip

To avoid IP blocking, use proxies while scraping Zillow data. Also, get rotating proxies if you plan to scrape in a larger scale. A rotating proxy makes it look like every request you send comes from a different IP address, which reduces your odds of being blocked by Zillow.

Conclusion

Scraping Zillow data is valuable for various real estate-related purposes—-from market analysis to property valuation. Using Python and scraping tools are distinct methods to execute the process. Whatever method works for you, both methods make scraping in real estate easier.

It is vital to be mindful of Zillow’s terms before scraping to avoid the website’s scraping precautions and legal consequences. Being responsible and cautious is a must when gathering data from Zillow.