A complete guide to extract real estate data from web
The real estate market is constantly expanding and with it, real estate agents and companies are trying to find new solutions to determine exactly what the future holds. While real estate generally doesn’t change dramatically overnight, it is impacted by too many factors for any one person or even organization to track.
So will prices go up or down? Which parts of the city are most in-demand? Are there facilities that simply need to be remodeled to increase prices quickly? These are just some of the questions real estate agents often ask themselves.
Answering these questions requires a lot of research data for comparison, and collecting so much information manually would be like hunting a wild goose. Here’s web scraping in action, collecting and structuring data as fast as you can:
As we all know, web scraping is the power of data mining! So if you want to learn more about why someone would want to extract real estate data from the internet and how to do it right, let’s continue our journey together. We have prepared both a DIY solution and a step-by-step guide on how Zillow Real Estate Agents Scraper can do this.
Use of web scraping in real estate
The main use of web scraping in real estate – creating your own comprehensive real estate database. Web scraping also allows this data to be updated daily as agents and property owners post new properties daily. It contains all the details regarding the property as well as the contact details of its agent/owner.
This data helps real estate agents find facilities that better meet client and budget needs. You can also monitor price trends, rental yields, etc. Depending on the situation and the available equipment. In short, the data gives real estate agents an edge in their business when selling or buying properties for their clients.
Property data that can be collected using web scraping
All data that is publicly displayed on real estate websites can be scraped. This contains:
– Real estate address
– Sales price, rental price
– Beds, baths
– Square, parking lots
– Furnishing
– History of prices and taxation
– Neighborhood Details
– Contact details of the agent, the owner
– Market days, year of construction, etc.
– Pictures
Intelligence analysis of real estate data
After scraping web real estate data, the next process is data mining. Real estate data mining refers to the phase of examining a large amount of aggregated data to come up with a valid idea.
To make the most effective decisions in the industry, real estate agents and businesses need to analyze consumer behavior and general patterns that are currently dominating the industry. Intelligent data analysis in real estate can serve several purposes:
Identifying market trends. Data scraping helps to analyze general trends such as total investment in real estate, individual income, etc.
A study of the time of real estate fluctuations. It helps to predict future fluctuations, identify its ground rules and characteristics, and identify the factors that affect them.
Customer management includes researching customers and their consumption habits, helping sellers learn new ways to interact with existing customers, and attracting new customers.
Start and export your property scraping project
Now our project is ready to scrape the real Estate sites. To do so, simply click on the green “Run Extractor” icon on the left sidebar.
For longer and larger projects, we recommend a test run to ensure your data is extracted and formatted correctly.
However, to begin the cleaning for this project, click the Run button.
As soon as United Lead Scraper has finished scraping the website, you can upload the extracted data as an Excel / CSV file or as a JSON file.
Final remarks
Now you know how to extract a property website like Zillow and others to create a list of properties for sale.
This list can be used to compare prices provided by customers and to understand the industry.
Note that some real estate websites prevent web scrapers from retrieving data.
If you need help with any of your projects, you can contact our customer support through our chat or contact page where they will be happy to help you!
