Data is gold in real estate. As the industry begins to get back on its feet, many realtors scramble to get verified data to grow their business. Moreover, there’s a myriad of data in the real estate world. These data include property, mortgage, construction project leads, residential real estate, foreclosed properties, expired listings, and For Sale By Owner (FSBO) listings.
Nowadays, artificial intelligence has made it possible to gather big data in real estate. Machine learning has been crucial in paving the way for the modernization of this industry to make both home buyers and sellers meet and settle for the right price through their real estate agents. Thus, these real estate agents rely heavily on data to get leads or prospects and turn them into buyers and sellers.
All collected data or leads are utilized by real estate agents when they execute their real estate campaigns. Real estate campaigns include expired listing, circle prospecting, FSBO, Foreclosure, and Geo-farming.
Moreover, the market’s exponential growth is due to how investors have turned to real estate. In the US in 2016 alone, the industry generated a market size of $82.05 billion, more significant than its performance in 2013 at $67.92 billion. More importantly, the industry generated a revenue of $76 billion primarily because of data availability through artificial intelligence in 2018.
Thus, you must consider that the internet is always your go-to source for just about anything. Every search you conduct on your laptop or mobile device is data for mining various resources. It’s been reported that many home buyers search the internet for prospective homes instead of driving around or checking classified ads.
If you’re a real estate agent who wants to grow your business, here are the top data collection trends you could utilize.
1. Free Data Gathering
If you’re starting in the industry and just getting the ropes of the business, you might not have as much capital. You don’t have to worry because you can extract data for free to use in your budding business. Whether you need statistics or demographics, you can always go to the Census Bureau of your country. This is a public domain that houses the information of the population.
The government utilizes the census to plan for building public infrastructures such as schools, hospitals, and bridges. Thus, it contains very vital and accurate information for realtors. A realtor would determine if a specific location would be viable for business through census data.
But since the census is covered by non-disclosure and confidentiality clauses, it will not give you access to the people’s private information, such as telephone numbers and email addresses. Although, relevant information such as name, address, age, marital status, occupation, and year of immigration will be available for you to use.
2. Machine Learning Tool
To assess an area’s liveable condition and the quality of public infrastructure within it, many industry specialists rely on machine learning such as three-dimensional mapping to check for the dilapidation report of an area. It can sum up the locations’ roads and asset conditions and determine their safety.
This report is also economically utilized to determine the market value of the real estate in an area. Real Estate experts can easily verify if a site is worth investing in through this report. The technology is also safer than getting actual people to conduct land surveys.
3. Utilizing Multiple Listing Service (MLS)
Even with the rise of artificial intelligence, manual data gathered and entered into the MLS still gives real estate agents a more accurate representation of data in their locality. Additionally, the MLS is an organization of brokers who mutually agree to share properties’ sale details. This is a members-only platform where cooperation among brokers is highly encouraged and commissions are shared for every successful sale.
The real estate market is tough to compete in but a tool such as the MLS somehow levels the playing field for small real estate brokerage and large real estate firms. Agents can give homeowners sound advice the same way large brokerage companies can.
4. Social Media
The exchange of vital information in virtual communities and networks in all social media platforms results in a gold mine of data for real estate agents. A simple hashtag search like #realestateforsale can yield a million leads. However, narrowing it down to your location will give you more specific data to work on. For social media, the information is right in your face. You just need to be creative and imaginative when you search for it.
5. Web Scraping
You can use a web crawler or a bot to fetch data in a web browser for a more tech-savvy real estate agent. Data scraping utilizing the Hypertext Transfer Protocol (HTTP) or simply put, the web browser is often used to extract data for indexing. Real estate agents use web crawlers to access information. This could be used to assess and evaluate property value, assess rental yields, observe vacancy rates, and forecast market direction to name a few.
6. Website Marketplace
The emergence of a website marketplace gives consumers front and centre information for all real estate details they need to purchase their first home. Buyers get a glimpse of the house as well with beautiful photos accompanying each property for sale. Real estate agents use these websites’ marketplace while conducting cold calling with prospects. This is to give them a clear picture of the homeowner’s property they want to sell or buy. The data in the marketplace is a source of valuable conversation between a realtor and a homeowner.
Technology has made it possible for a business to reach greater heights. Accessibility to big data has made all facets of any business grow. Digitization resulted in a more accurate and speedy data gathering. This transformed many businesses and not just real estate to restructuring their industry to adapt to modern times.
Accessibility to relevant data allows real estate managers to make evidence-based decisions that are far likely to succeed than any other method. Machine learning also allowed many industries to predict more accurate outcomes, thus generating larger profits in the long run.