How Property Agents and Investors Are Leveraging Big Data (2024)

Using the internet to search for real estate is the new norm. Ninety percent of home buyers begin their search online, and there’s been a staggering 253% increase in real estate-related searches in the last four years.

This means there’s a ton of data out there for real estate agents, which is great. However, sifting through it all to find opportunities can be arduous and similar to finding a needle in a haystack.

Web scraping and automation are viable solutions to this problem and can supply you with key real estate data. Here are some specific ways you can use these techniques to gain an edge over your competitors.

Why Is Web Scraping Being Used by Real Estate Agents

Web scraping, a process that extracts data from websites, allows you to collect valuable information you can use to identify hot leads and guide your decision-making. This data can come from several different sources such as property listings, seller profiles, property prices, and so on. Some specific data elements to scrape, according to Scrap.works, include:

  • Property and price data
  • Property size
  • Rent price
  • City, state, and zip code
  • Reviews
  • Agent information

After obtaining this data, real estate agents can use it for several different purposes, such as making smarter investment decisions. Real estate data is notoriously hard to find when using conventional resources like government and competitor sites, but it becomes much easier when aggregating it from these types of sources.

By amassing relevant, up-to-date data, you can perform in-depth analysis to identify which properties are most worth investing in. This increases the odds of a positive return on your investment – and seeing the return in a timely manner.

Another application of web scraping is using it to determine the price when selling a property. Aggregating data from a variety of different resources allows a real estate agent to come up with a fair price in relation to comparable properties in the area. This is beneficial to buyers because they get a good deal, and also to you because it helps you sell a property more quickly.

You should also note that the web scraping process has evolved significantly in recent years. Web data integration is a newer, more robust solution that provides a means of cleaning, optimizing and preparing a large volume of data.

In turn, it’s much easier to consume and provides intuitive reporting for easy analysis. This allows you to exercise quality and control over the data, transform, and normalize it all within a single platform.

Streamlining Real Estate Process

When it comes to hiring, automation can be a tremendous asset to real estate agents. The average time to fill a position in the U.S. was quite lengthy at 43 days in 2019. Anything you can do to streamline this process and find top industry talent saves you time and money. And using automated hiring tools allows you to do just that.

One of the most commonly-used tools is an applicant tracking system, which allows real estate agents to filter applications using criteria like skills, keywords, years of experience, and so on. If you receive a high volume of applications, you can quickly filter through the candidate pool to find the candidates that are best suited for the position and that meet your specific criteria.

Automated emails keep applicants informed throughout the hiring process. You can keep them up to date on their status, let them know if they’re still being considered for the position, or if you’ve chosen to move forward without them.

Scheduling interviews is another example of how hiring can be streamlined with automated recruitment apps. Trying to find a time slot that fits everyone’s schedule can be tricky, but with the right software, you can seamlessly coordinate schedules and align calendars to automatically select an interview time that works for all parties.

Besides that, automation can help with onboarding. You can create automated workflows where new hires receive onboarding materials like welcome emails, orientation information, training guides, and relevant contact information in a logical sequence. This ensures that new hires have the necessary information to get started while requiring very little manpower.

Big Data and Sales Intelligence

When combined, these two forms of technology can be also used for competitive analysis. For example, you can use crawling software to quickly determine which keywords top competitors are ranking for. From there, you can analyze their landing pages to see what techniques they’re using to rank highly and replicate their strategy.

On the flip side, you can also identify pages search engines are ignoring to figure out what they’re doing wrong. Rather than laboriously dissecting their site on your own, automation and web scraping offer a complete picture of a competitor’s link profile with minimal effort.

Another example is using automated web data collection to detect when prospects complete an action that indicates a change in lead status. One case study details how a financial services firm defined and tracked sales leads and fed the data into a web data integration solution.

The updated data was then fed to the company automatically where leads were either updated or eliminated daily for optimal sales intelligence. As a real estate agent, you could follow a similar strategy to keep tabs on prospects throughout the sales cycle and capitalize on leads while they’re hot.

Finally, it can be used to instantly compare prices on property listings with key competitors. Get a quick snapshot of the pricing strategies they’re using, and stay up-to-date on any promotions they offer to determine what’s helping them increase business. You can then use this information to shape your own strategy and reel in more customers.

Final Remarks

There were 1.3 million real estate agents in the U.S. in 2018, up 6% from 1.22 million in 2017. Competition is fierce in many markets, and anything you can do to gain an edge is helpful.

One of the best ways to do that is by utilizing cutting-edge technology like web scraping and automation. It can be used for everything from making smarter investment decisions to hiring top talent and performing in-depth competitive analyses.

Which specific aspects of your business are you looking to streamline? Share in the comments below.

This article has been contributed by Luke Fitzpatrick.

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How Property Agents and Investors Are Leveraging Big Data (2024)

FAQs

How Property Agents and Investors Are Leveraging Big Data? ›

Analyzing and Monitoring Market Trends: Data analytics is crucial in understanding market trends and the impact of various factors on real estate prices. Anticipating Future Growth: Data analytics helps uncover patterns correlating with real estate growth, aiding in future projections.

How do real estate investors use leverage? ›

Leverage uses borrowed capital or debt to increase the potential return of an investment. In real estate, the most common way to leverage your investment is with your own money or through a mortgage. Leverage works to your advantage when real estate values rise, but it can also lead to losses if values decline.

What are the 5 P's of big data? ›

In this article, we define the 5P of D&A measurement, i.e., purpose, plan, process, people and performance. These rules can help enterprises in measuring business outcomes in a reliable manner, avoid some of the common mistakes and achieve better business outcomes.

What is big data in real estate? ›

Big data allows real estate agents to analyze vast amounts of historical data to predict future trends and make informed decisions about buying and selling properties. Real estate agents play a crucial role in the buying and selling process of a property.

What data do real estate investors look at? ›

Here, we go over eight critical metrics that every real estate investor should be able to use to evaluate a property.
  • Your Mortgage Payment. ...
  • Down Payment Requirements. ...
  • Rental Income to Qualify. ...
  • Price to Income Ratio. ...
  • Price to Rent Ratio. ...
  • Gross Rental Yield. ...
  • Capitalization Rate. ...
  • Cash Flow.

What is an example of leverage in real estate? ›

To calculate your leverage ratio in real estate, divide your debt by your equity. For example, if your mortgage is $300,000 and your equity is $100,000, then your ratio is three and can be considered good.

What is the best way to leverage real estate? ›

Here are some options:
  • Home improvements. It can be a smart move to leverage real estate equity to cover your next home improvement project, though not all improvements offer the return on investment you may be looking for. ...
  • Real estate investing. ...
  • Higher education expenses. ...
  • Medical expenses. ...
  • Debt consolidation. ...
  • Refinance.

What are the 4 V's of big data in brief? ›

There are generally four characteristics that must be part of a dataset to qualify it as big data—volume, velocity, variety and veracity. Value is a fifth characteristic that is also important for big data to be useful to an organization.

What is one of the potential dangers of using big data? ›

If the data is not driven and interpreted in the right direction, risks to the information can lead to catastrophic and inaccurate results regarding sales projection, trending analysis, and cost drivers.

Why is big data needed in the modern world? ›

The importance of big data in today's world

Big data has become a driving force behind many business strategies and decision-making processes. Its importance lies in its ability to provide valuable insights, enable informed decision-making, and drive innovation.

How is data used in real estate? ›

With data analytics for real estate, brokers can keep track of which companies and brokers are listing and selling the most, how they rank for customer satisfaction, and more.

What is are the key property properties of big data? ›

The 5 V's of big data -- velocity, volume, value, variety and veracity -- are the five main and innate characteristics of big data.

What is the use of data analysis in real estate? ›

The Importance of Data Analysis in Real Estate

They allow professionals to effectively predict real estate values, find and evaluate opportunities, assess risks, and plan development.

How do investors use data? ›

For example, analyzing historical price trends and market data can help investors make more informed decisions about when to buy and sell assets.

Where do investors get their data? ›

Probably the most useful sources of information, corporate filings provide investors with information detailing companies' financial health, future prospects and past performance. This is the kind of information you need to judge whether certain stocks, bonds or mutual funds are smart investments.

What will leverage allow an investor to do? ›

Leverage allows the investor to either purchase a property that costs more than the amount of money they have available or to spread out that cash across multiple properties. It also has the potential to increase returns by allowing investors to purchase more expensive, but potentially more profitable, assets.

How does leverage applied to investments? ›

Leveraged investing is a technique that seeks higher investment profits by using borrowed money. These profits come from the difference between the investment returns on the borrowed capital and the cost of the associated interest. Leveraged investing exposes an investor to higher risk.

When investors use leverage in their own portfolios? ›

This means that the investor may be able to use their remaining capital to make other investments and diversify their portfolio. For example, if an investor wanted $10,000 worth of exposure to one particular share, the investor could borrow $10,000 and only pay the interest expense of, for example, $1,000.

How can leverage be used to make money? ›

Leverage is the strategy of using of borrowed money to increase investment power. An investor borrows money to make an investment, and the investment's gains are used to pay back the loan. Leverage can magnify potential returns, but it also amplifies potential losses.

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