Scraping Real Estate Websites for Property Data

Real estate data scraping is also known as real estate data extraction or web harvesting. It enables you to extract data from real estate websites or any other digital source. You won't need to check every item in the property listing manually, glance through the search results page, type the search result URL in the address bar of your actual browser, and so on. The process of working with real estate listing data becomes automated so that real estate data collection will require minimum time and effort. The essential tools of web scraping are known as crawlers or scrapers. They parse real estate listings URLs and apply search patterns to them.

Why Does the Real Estate Industry Need Data Scraping?

Companies that scrape real estate data get a meaningful competitive edge over their business rivals. It's a 100% legal method because the data is obtained from the public domain (you can easily access it without scraping). Here are a few examples of property data that real estate agents might want to scrape:

• Property type
• Property agent
• Images
• Address (City/State/ZIP Code)
• Property size
• Parking spaces
• Bedrooms number
• Current price (sale price/rental price)
• Rental yields
• Customer reviews
• Other property details
• Crime and safety statistics
• Foreclosure and auctions listings
• Urban planning and construction permits (the last three data fields might be available only in the advanced mode)

After you have identified the main data points, the scraping process begins. At its initial stage, software scripts collect raw data from multiple online sources. They extract facts and numbers from real estate listings, Zillow, Trulia, and other websites with publicly available data. Once the gathering process is finalized, the web scraper presents search results in a structured format so that you get usable data. You'll be able to systematize all the data that is relevant for your property listings as a CSV file, a set of Excel files, or in some other format.

What Happens After the Extraction

The next step after extraction is real estate data mining that enables you to get actionable knowledge. Based on web data, you'll be able to identify property market trends, research fluctuation periods, and detect the factors that cause fluctuations. Plus, you can improve your client management, enhance your email marketing and start to send custom alerts through emails.

Data mining might employ a wide range of methods, such as data preparation and cleaning, classification, clustering, tracking patterns and revealing anomalies, decision trees and so on.

Web Scraping Use Cases in the Real Estate Market

Consulting firms real estate, agencies, and aggregators might benefit from scraping in the following ways.

• Obtain real-time intelligence and share it on their one-stop-shop website for consumers' benefit. This should impress their already existing and future customers.
• Forecast market direction to make better business decisions and outline more profitable business strategies. Such metrics as const properties, const price, closing price, flight prices, and so on mean a lot to the professionals of the industry.
• Monitor competition. Competition about marker changes is one of the crucial factors for the sector. The better you know the rivals, the easier it should be for you to attract new clients and close more deals.
• Monitor vacancy rates. You might want to invest in an old building rather than a new project because the former might turn out to be a diamond in the rough. But if you make a mistake, it might incur large losses. The current vacancy rate is the telltale parameter that allows you to assess the potential of the building.
• Accurately deduce your property's value. When selling your childhood home, you should do some market research to estimate its true value. Thanks to scraping, you won't need to contact sales managers to define the optimal price tag.
• Maximize rental yield. The rental yield of different properties in the same neighborhood might value drastically. You can find out which property types are most common in a given region and have the highest ROI.
• Make the most of real estate investments. When choosing residential or commercial properties for investment purposes, most buyers strive to find the best deal on the market. Scraping will provide you with precious investment analysis data.

These were just a few examples of how scraping-related technology advancements can influence the workflow and business values of companies from the real estate sector. In the future, the impact of this technology is only likely to increase. Once you try scraping a couple of times, you should appreciate its fast speed, accuracy and ability to handle huge amounts of data.

Tools for Scraping Real Estate Websites

You can choose from two types of extraction tools: build a custom one or outsource a scraping real estate listings solution. If you opt for the former, you'll have to write the source code from scratch and you'll need proxies to support your web scraping tool. Proxies allow you to collect web data from property listings or any other websites under numerous IP addresses. Before choosing a full stack developer, you should carry out a thorough price comparison, check the company's portfolio and read customer stories about it.

Many companies that specialize in selling and buying properties might not want to handle ever-changing technology trends themselves. They just need expert knowledge to better analyze consumer behavior and boost their income. If this is your case, you can outsource estate data scraping services. All you need to do is open a web scraping solution in your browser tab and get high-quality data. You'll receive such data at an affordable price and in the shortest possible time.

If you prefer outsourcing, you won't need to collect information about properties for sale. You'll get access to already accumulated basic knowledge from multiple sources and you can rely on it to draw data-backed business insights.

What Can We Offer to a Company That Needs Exhaustive and Up-to-Date Real Estate Data

We can proudly say that we have accumulated a large and detailed database of useful statistics. We will be glad to share our knowledge with you. If your real estate business needs valuable information quickly and at a sensible cost, we could recommend that you follow these simple steps:

1. You let us know your email address and the characteristics of real estate industry data that you need. You might want to share an address selection with us, the link to your favorite real estate website, a listing of several websites, or any other details.
2. We'll promptly get in touch with you and discuss the specifics of scraping real estate data on demand.
3. We create a real estate scraper for you and collect information from an extensive list of properties.
4. We send you a sample of extracted data and you pay us only if you find that sample worthy.
5. We scrape real estate data in full measure and provide you with a vast amount of information.
6. If you want us to update the information regularly, let us know whether you would like us to send you files or let you access our databases. If you wish, we can work with Google Cloud Platform, Amazon AWS, and other cloud-based databases.

We can guarantee that you'll make the most from Zillow, Trulia, or any other listing on the Internet that you want to explore. Even though our solution is not fully automated yet, it is one of the most reliable on the market. If you have any questions about how it functions, feel free to contact us at any moment.

Final Thoughts

Hopefully, this article came in handy and now you better understand how to meet your real estate web scraping needs. Thanks to this business approach, you'll be able to extract basic property details about any object from real estate listings. Web scraping real estate should give a considerable competitive edge to your business. Instead of building custom web scrapers, you might consider using our real estate data solution that is affordable, cost-efficient and highly reliable.