As the internet continues to grow, the amount of data it generates grows with it, opening new opportunities to improve processes and make more informed decisions.

Real estate is one of the many industries that are being disrupted by data-related technologies and innovations.

Whether you are a broker, realtor, investor, or property manager you have the potential to become data-driven and gain invaluable insights from real estate web scraping.

In this article, you will see the many ways real estate data can help you and how utilizing web scraping can help you and your organization become disruption-proofed and fully prepared for the world of tomorrow.

What is the use of a web data extractor?

There is more public data available in the real estate market than ever. There are numerous listing sites, endless data points available for everyone to see. And if there’s data, there should be a way to learn something new from the data to make better decisions. But there’s one big problem...

It’s hard to get the data in a structured way. But you need to get the data first, to gain insights.

Unfortunately, many websites don’t provide APIs. Or even if they do, you might not get all the data you want only in a limited fashion.

But still, the publicly available data is there, you just don’t have a straightforward way to get the data.

This is where web data extraction comes in. Web data extractor software allows you to get this publicly available real estate data at scale.

Using the correct tools or partnering with a data scraping partner, like Zyte , allows you to tap into the world of web scraping and enjoy the benefits of high-quality data.

5 ways real estate data extraction can help you

1. Appraising property value

There are many situations where estimating the value of a property is necessary. Maybe you’re trying to list it online for the most accurate price, maybe you’re trying to get financing or you’re analyzing a property before purchasing.

You want to get the most accurate value of how much the property is worth.

Being in the real estate market means that you have a lot of competition. In order to be ahead of the competition, you need to find ways to know more than others.

As most realtors get their data from a single listing like the MLS, you can differentiate yourself by accessing alternative data sources. Web data extraction can help by allowing you to fetch structured real estate data from any publicly available listing website.

And as web scraping is a new technology for many, it can give you huge value as you will have considerably more data, and thus, information, in your hands.

With web scraping, you can gather all the data points that exist about the given property, if it’s available online.

Then, you can use this data to justify your price or position your offer more accurately.

Because you see the full picture through web data, you have a better chance to accurately estimate the value of a property.

2. Location, location, location

You may have heard this mantra from agents and realtors. Location is one of the key factors that determine the value of a property.

Unfortunately, it’s not straightforward to get access to structured real estate data from only that specific area you want to analyze.

With web scraping though, you can automate the process of filtering through data so you only extract data that matters to you.

Or you can just grab the whole market data from the web then filter the data yourself, depending on your requirements.

3. Raw numbers over emotions

When it comes to properties, there are many numeric data points that can influence the price: square footage, age, lot size, last sold price, etc.

When buying a property for yourself, emotions play a huge role in your decision-making. Sometimes you are willing to pay more because you have strong emotional reasoning.

But also, it is always important to look at the raw numbers of a property before purchasing. You can make smarter - and more logical - decisions if you first look at the raw data and make a data-driven decision.

Especially when it’s a property you purchase for investment purposes. Without web scraping, you cannot see the full market’s prices and other data points in a structured way.

4. Vacancy rates

When buying a property for investment purposes, the vacancy rate is a crucial factor that can be a dealbreaker or even one of the main reasons you purchase a property.

If the vacancy rate goes down in a market, the rents are expected to increase because the demand is higher.

On the other hand, if the vacancy rate goes up that means the demand is lower so the rents are expected to decrease.

Unfortunately, many agents use a static vacancy rate when analyzing a property and disregard the actual data. They do this, simply, because they don’t have time to do the research themselves.

Fortunately, with the help of web scraping, it doesn’t take that much time to gather high-dimensional data about the real estate market and calculate the expected vacancy rate more accurately.

Collecting fresh pricing and rent data, along with recent property completions and calculating lease lengths can help you to determine vacancy rates.

5. Market direction

The real estate market is always changing, going through cycles. The challenge is to identify where it’s going right now and where it will be in the future. Understanding market direction is important to properly value property and to make investment decisions.

These insights lie in the raw data of the real estate market. It would be impossible for an individual to gather all the data manually.

That’s why web data extraction can provide so much value by giving you all the data there is, in a timely manner.

Also, if you start monitoring the real estate market today with the help of web scraping, in the upcoming months and years you will have a tremendous amount of historical data.

Mining this data can help you see the direction the market is moving towards and show you patterns you wouldn’t have been able to recognize otherwise.

Process and challenges of scraping real estate data

Scraping real estate data can seem simple at the beginning. These are the general steps if you decide to do it yourself:

1. Identify target website(s)
2. Determine what data points you want to extract
3. Create a scraper with a tool like Scrapy
4. Store the data in a database
5. Mine the data to get insights

You will need to extract a lot of data regularly if you want to get the most insights. For this, you need to extract data at scale. There are many challenges and hurdles you need to go through if you decide to extract data from the web on a large scale.

Main challenges:

• Scraper maintenance
• Javascript rendering
• Proxy management
• Data quality

Solving all these challenges takes a lot of resources and technical experience in web scraping. Unless web scraping is the core of your business (probably not), you might be better off partnering with a vendor that can solve these problems for you, so you only get the quality data but don’t have to deal with the hurdles.

Learn more about real estate data extraction

Scraping real estate data has huge potential for anyone who is in the real estate market. Especially because for many this is still an untapped opportunity.

Also, the web data extraction tools you can choose from have evolved a lot in the past years so either you do it yourself or partner with a web data scraping company like Zyte , you will be in a great position to start gaining value from public web data and get a competitive edge.

If you want to learn more about how to make the most out of real estate data, download our whitepaper here: Fueling real estate’s big data revolution with web scraping