7 Best Real Estate Scrapers 2024: How to Scrape Property Listings Data

The real estate industry relies heavily on data. From listing prices to property details, key information can provide realtors, investors, and homeowners with valuable insights. However, collecting this data manually is tedious and time-consuming. This is where real estate web scrapers come in.

Realtor web scrapers automatically extract data from real estate listing websites. This saves hours of manual work and provides access to large datasets for analysis. With the right scraper, you can easily collect property data on a massive scale.

In this guide, we‘ll cover the top 7 real estate scrapers of 2024. We‘ll look at their key features, pros and cons, and pricing. We‘ll also provide a step-by-step tutorial on how to scrape real estate listings data.

Overview of the Best Real Estate Scrapers

Here are the top real estate scrapers to consider in 2024:

1. ScraperAPI – The best overall real estate scraper. Extremely fast, accurate, and easy to use.
2. Brightdata – Powerful data collection with browser and proxy support. Ideal for large-scale scraping.
3. ParseHub – Intuitive web scraper with a point-and-click UI. Great for beginners.
4. Octoparse – Easy to use visual scraping and built-in data management.
5. Dexi.io – Affordable web scraping API with excellent documentation.
6. Scrapy – Open-source Python scraping framework. For developers.
7. Apifier – Scalable web scraping platform with actor-based architecture.

Next, let‘s look at the key features and use cases of each real estate scraper in more detail.

1. ScraperAPI

ScraperAPI is one of the most popular and versatile real estate scrapers available. It‘s a paid API service that handles all the difficult parts of web scraping for you.

Some key features of ScraperAPI:

• Automatically scrape any site – realtor.com, Zillow, etc.
• Fast and accurate data extraction.
• Easy to set up with no coding required.
• Schedule and automate scraping runs.
• Integrates scraped data into apps via API.
• Free plan available.

ScraperAPI is extremely beginner friendly. You don‘t need any programming knowledge to extract data. Their Chrome extension lets you turn any web page into an API endpoint with a single click.

The service is also blazing fast. ScraperAPI can extract listings data from even the largest real estate sites in seconds. For large scraping projects, you can run concurrent scraping jobs to collect data even quicker.

ScraperAPI is a great choice if you need to pull real estate data into spreadsheets, apps, databases, or other software. With their API, you can build automated workflows to keep your data updated.

Key Use Cases:

• Quickly build real estate datasets for analysis and lead generation.
• Feed listing data into MLS software, CRMs, etc.
• Monitor listing prices and trends on key sites.
• Research agents, brokerages, and market inventory.

Pricing:

ScraperAPI has a free plan which lets you make up to 500 API requests per month. Their paid plans start at $39/month for 5,000 requests. Volume discounts are available.

They also offer a 7-day free trial so you can test out their service risk-free.

2. BrightData

BrightData (formerly known as BrightLink) is another powerful web scraping solution. Their key strength lies in proxy management.

BrightData lets you scale up your scraping operations with millions of residential and datacenter proxies. This allows you to bypass restrictions and scrape data at massive scale.

Some notable features:

• Millions of rotating proxies to avoid IP blocking.
• Automatic CAPTCHA solving for smooth scraping.
• Real browser and mobile scraping options.
• Integrates with Python, R, JavaScript and 100+ tools.
• Free plan has 50 monthly scrape requests.

The proxy network gives BrightData a leg up for scraping stubborn real estate sites. You can scrape continuously without worrying about your IP getting blocked.

BrightData also offers browser-based scraping through real Chrome and Firefox browsers. This allows you to render JavaScript and scrape interactive sites that API scrapers may struggle with.

Between proxies and browser scraping, BrightData is a top choice if you need to extract real estate data from highly restrictive sites. The volume of data you can collect is virtually unlimited.

Key Use Cases:

• Scrape multiple large real estate portals at scale.
• Collect data from restrictive sites like Zillow and realtor.com.
• Build massive datasets by scraping continuously with proxies.

Pricing:

BrightData has a free plan for testing. Paid plans start at $99/month for 50k monthly scrape requests. Enterprise pricing is also available.

3. ParseHub

ParseHub is a visual web scraper – instead of writing code, you point and click to extract data. This makes ParseHub one of the easiest scrapers to use for beginners.

With ParseHub, you visually configure a scraping campaign through their web interface. Some key features:

• Visual editor – no coding required.
• Automatically extract tables and data.
• Scrape dynamic content powered by JavaScript.
• Schedule and automate scraping runs.
• Integrates through API, Zapier, or exports like CSV.

The visual editor lets you highlight and select the data you want to extract from a web page. ParseHub will automatically determine the underlying patterns and scrape data accordingly.

You can configure scrapers to deal with pagination, filters, infinite scroll, and other complexities with just a few clicks. This makes ParseHub ideal for scraping inconsistent real estate sites.

Once your scraper is set up, ParseHub can output the scraped data to CSV, Excel, JSON, databases, apps via API, and various business tools through Zapier integration. Scheduling recurring scrapes is easy.

Key Use Cases:

• Quickly build scrapers without coding knowledge
• Scrape complex, dynamic real estate sites
• Frequently update MLS and CRM data
• Monitor listing prices and analytics

Pricing

ParseHub has a free plan which lets you scrape 500 pages per month. Paid plans start at $99/month for 5k page scrapes.

4. Octoparse

Octoparse is another code-free visual scraping tool. It focuses heavily on data organization and cleansing flows.

Some useful features:

• Visual web scraper builder
• Built-in data processing and cleansing
• Output data to CSV, Excel, etc.
• Cloud-based scraping distributes workload.
• Free trial with 50 extract requests.

Octoparse allows you to set up scrapers without writing any code. You can visually highlight data, set up pagination scrapers, implement filters, and more.

Once scraping is complete, Octoparse has built-in tools to process, clean, and transform the extracted data. You can merge, deduplicate, reformat, and filter your datasets before exporting.

This combination of visual scraping and data preparation makes the tool useful for scraping inconsistent real estate data from various sources. The workflows help minimize time spent cleaning data before analysis.

Key Use Cases:

• Aggregate real estate data from multiple websites
• Clean and process extracted data for analysis
• Build datasets without coding experience
• Frequently update CRM and MLS data

Pricing:

Octoparse has a free trial with 50 extract requests. Paid plans start at $299/month for up to 10,000 extract requests.

5. Dexi.io

Dexi.io offers an affordable and beginner-friendly web scraping API service. The API is language agnostic and easy to implement.

Here are some highlights:

• Simple API integration – no scraping knowledge needed.
• Affordably priced for small businesses.
• Fast and reliable data extraction.
• Excellent documentation and support.
• Free plan available up to 200 API calls/month.

For basic real estate scraping tasks, Dexi provides an easy API option to collect data. No browser automation or complex scraping logic is required on your end.

The service is relatively affordable, with plans starting at $9/month for 1,000 page scrapes. This makes it one of the cheapest paid scrapers.

Dexi‘s documentation and tutorials help you get scraping quickly, even without prior experience. Support is very responsive as well.

Key Use Cases:

• Quickly extract real estate data through API calls
• Affordable scraper for small companies and agencies
• Scrape basic listings data from common real estate sites

Pricing:

Dexi has a free plan for 200 API calls/month. The Starter paid plan is $9/month. Pro plans offer more features and larger request volumes.

6. Scrapy

Scrapy is an open-source Python scraping framework for developers. It is extremely fast but involves coding your scrapers.

Some notable features:

• Lightning fast asynchronous scraping
• Powerful selector toolchain and extraction libraries
• Open source and customizable
• Build scrapers with Python scripts
• Great for large-scale and complex scraping

Scrapy doesn‘t have a visual interface. You write Python scripts to develop your real estate scrapers. This allows Scrapy to run extremely quickly while providing fine-grained control.

The framework is very extensible. You can integrate scrapy with all major Python data analysis and machine learning libraries.

Overall, Scrapy is ideal for developers who want to build highly customized, large-scale scraping solutions. The coding requirement makes it unsuitable for non-technical users.

Key Use Cases:

• Build complex scraping solutions with Python
• Orchestrate scrapers across multiple sites
• Continuously scrape large volumes of real estate data
• Leverage scraped data with Python for modeling and analysis

Pricing:

Scrapy is an open-source framework available for free. You will need to pay for cloud servers if deploying large scrapers.

7. Apifier

Apifier offers a web scraping platform focused on scalability and automation. The tool revolves around so-called "actors".

Some useful features:

• Automate scrapers via actor architecture
• Run scrapers headlessly on virtual machines
• Scale up on cloud infrastructure
• Integrates with Zapier and webhooks
• Free community plan available

The actor model allows you to encapsulate and automate entire scraping workflows. Actors can trigger each other, providing an easy way to orchestrate complex flows.

Apifier scrapers run on virtual machines for reliability and scalability. You can add VMs to distribute load and scale data volume.

The platform combines scalable infrastructure with an easy-to-use interface. Apifier is great for automating real estate data collection and processing pipelines.

Key Use Cases:

• Automate scraping of multiple sites
• Orchestrate scraping into data processing workflows
• Run large scrapers in the cloud
• Continuously collect real estate data

Pricing:

Apifier has a free community plan. Paid plans start at $99/month for advanced features and more compute power.

Key Factors When Choosing a Real Estate Web Scraper

With so many scrapers to choose from, how do you select the right tool? Here are some key factors to consider:

Ease of Use

Look for an intuitive scraper that matches your technical abilities. Code-free visual tools like ParseHub are great for non-developers. APIs like ScraperAPI and Dexi are also beginner-friendly. Scrapy requires Python coding skills.

Data Volume

Consider the amount of data you need to scrape. Tools like Scrapy, BrightData, and Apifier can handle large volumes through coding, proxies, or cloud computing. Other scrapers may involve pricing limits.

Data Processing

Some scrapers like Octoparse have built-in data organization and cleansing features. Others focus solely on extraction, leaving you to clean data externally. Choose what meets your workflow needs.

Customization

As an open-source framework, Scrapy allows for extreme customization in your scrapers. Other tools have predefined functionality but let you adapt to some degree.

Support and Documentation

Look for thorough docs and responsive customer support. This ensures you can get help when developing and running scrapers.

Pricing

Scraping tools range from free open-source (Scrapy) to enterprise platforms costing thousands a month. Choose a scraper that fits your budget constraints.

By evaluating these factors against your specific needs, you can narrow down the real estate scraper likely to work best for you.

Step-by-Step Tutorial: Scraping Listings from Realtor.com

To demonstrate real estate scraping in action, let‘s walk through extracting listings data from realtor.com using ScraperAPI.

Step 1 – Sign up for ScraperAPI

First, create a free ScraperAPI account. Confirm your email to activate your account.

You‘ll have 500 free API requests to start – no credit card required.

Step 2 – Get Your API Key

Log into your ScraperAPI dashboard. Under the API Keys tab, copy your default API key. We‘ll use this shortly.

Step 3 – Add the ScraperAPI Chrome Extension

Install the ScraperAPI Chrome Extension. This will automatically detect data on web pages and integrate the API.

Step 4 – Visit a Realtor.com Listings Page

Now go to realtor.com and search for active real estate listings in a neighborhood. Copy the URL of the search result page.

For example:

https://www.realtor.com/realestateandhomes-search/San-Francisco_CA

We will scrape some listing data from this page.

Step 5 – Extract Data with the ScraperAPI Chrome Extension

With your listings URL open in Chrome, click the ScraperAPI browser extension icon. Select the data you want to scrape from the page:

• Listing title
• Price
• Bedrooms
• Bathrooms
• Square footage

The extension will automatically detect and highlight relevant fields. You can reselect data if needed.

Finally, click ‘Scrape Page‘ to extract the data.

Step 6 – Output the Scraped Data

After scraping, you‘ll see the extracted data displayed. You can now output it in multiple formats:

• API – Returns the data as JSON through ScraperAPI‘s API.
• CSV – Exports a CSV file containing the scraped data.
• Google Sheets – Adds the data to a connected Google Sheet for analysis.

Let‘s output the scraped real estate listing data to a CSV file. Copy or download the output CSV.

And that‘s it! In a few simple steps, we extracted key details on realtor listings with ScraperAPI. You can now import the CSV into Excel, Google Sheets, and other apps for analysis and processing.

Next Steps and Ideas After Scraping Real Estate Listings

Now that you‘ve scraped sample real estate data, what next? Here are some ideas:

• Analyze listing prices, inventory trends, days on market, etc.
• Enrich your MLS database by importing scraped listing details.
• Build a pricing comp database based on currently listed homes.
• Scrape agent details to find seller‘s agents and build outreach lists.
• Scrape rental listings to analyze pricing and demand.
• Continuously scrape sites like Zillow to monitor price changes and new listings.
• Expand to redevelopments, auction sites, and international portals.
• Feed data into predictive pricing and lead scoring models.

The applications are endless! With the fundamentals learned, you can scrape from virtually any real estate website. Combined with data science libraries like NumPy, Pandas, SciKit Learn, and TensorFlow, the scraped data can drive all sorts of insights.

Frequently Asked Questions

Here are some common questions about real estate web scraping:

Is web scraping legal?

In most cases, yes. Gaining unauthorized access to data can violate computer hacking laws. But scrapers only access public data on websites. Scraper usage terms vary by site, so check policies.

Can sites detect scrapers?

Sites may notice suspicious traffic coming from an IP address. Using proxies and reasonable request patterns helps avoid detection.

How can I scrape data behind a login?

Some scrapers like Puppeteer allow browser automation to log into sites before scraping. You can also request login access from sites as an approved partner.

What happens if I reach my scraper‘s request limit?

Paid scraper plans can be upgraded to allow more requests. Free scrapers like ParseHub limit you each month. Slowing request rates or rotating IPs can help stretch limits.

Can I get blocked even on paid scrapers?

It‘s rare on well-maintained services, but possible if you violate terms of use. Reasonable scraping patterns minimize this risk. Proxies add another layer of protection from blocking.

Power Up Your Real Estate Business with Web Scraping

Scraping real estate websites unlocks game-changing data insights for brokers, investors, lenders, and more. After reading this guide, you should have a solid grasp of the top real estate scraping tools.

Look for an option that fits your use case, budget, and technical needs. Implement it for listings data, analytics, lead generation, and other applications.

Scraped real estate data can provide a true competitive edge. Combine it with data science techniques to take your business to the next level.