How big data is impacting real estate buying, selling and developing

Global big data has entered explosive growth. Humans have entered the ZB era (1ZB = 1024 × 1024 × 1024 × 1024GB) since 2012. Social media, mobile devices, wearable devices, corporate information, etc. generate massive amounts of data at all times. From the perspective of social media alone, the amount of data generated in one hour is equivalent to the data for a whole year in 2000.

Big data has subverted the business models of the retail, finance, and tourism industries before COVID-19. As an “invisible” infrastructure big data played a huge supporting role in epidemic monitoring and urban management during the lockdown. Big data will serve as an important component of the new infrastructure that has been greatly developed in the future.

For China’s real estate industry, which has always relied on national policies and limited data to make decisions, it is somewhat overwhelmed by the wave of big data.

“The real estate industry has been lagging in adopting new tools and technologies, as well as the use of big data,” said John Angelo, head of the Deloitte real estate department in New York, USA. “But I found that more and more real estate practitioners have begun to value the use of data and analysis in actual work in the last year and a half.”

Today, more and more high-tech companies and real estate giants are turning to big data and artificial intelligence, hoping to obtain more decision-making basis on real-time insights of data, such as location choosing, house pricing, buyers attracting.

1 Big data: newer, finer-grained data

General information about real estate, such as house type, location, transaction price, regional population growth trend, nearby education, supermarket, etc., these are listed on the US real estate transaction platform.

Big data in the real estate field does not refer to these traditional data (above information) but refers to newer and more detailed information. For example, the amount of day-lighting of the house, the noise pollution index of the area, which entertainment places in the surrounding area are more popular, and which fitness equipment residents prefer.

These big data can help the real estate industry to answer the most basic and difficult questions, what’s more, it can help buyers make purchase decisions better.

2 Big data: the basic of house pricing

Pricing is a very important part of the real estate industry. Real estate agents and developers usually rely on regular market data (such as the current supply of the housing market and past sales) and house conditions for pricing. Developers also need to consider construction costs. Over-pricing or under-pricing means that the home may be difficult to attract buyers.

Among all kinds of house pricing, high-end residential pricing is the most difficult. Because many facilities of high-end residences are customized, it is difficult to find reference house prices in the market. The pricing of high-end housing has always been subjective, and real estate agents have also struggled with it. So they pin their hopes on big data and artificial intelligence algorithms to solve this problem.

Usually, we use data analysis and artificial intelligence to analyze the various elements of the house to evaluate the quality and pricing of the house. But (like the pain point of real estate agents) there is too little reference data for high-end residential. The current chief technology director of Compass, Joseph Sirosh, said that when reference data is lacking, technology can make full use of existing data for analysis and pricing, and it is better to find price standards than people.

3 Big data: empower the process of house selling

Typically, luxury real estate agents use their social intercourse to sell their houses and only publish information for those few buyers who have purchasing power. Because this social intercourse is too small, for high-net-worth customers, it is not conducive to facilitating real estate transactions.

Rex is a digital real estate agency headquartered in the United States. They are keenly aware that technology is more conducive to the sale of luxury homes.

The company’s chief technical director Andy Buckett said: “We found this in selling high-end homes.” “We have a huge advantage in being able to advertise to global buyers. We can find buyers in other countries because big data doesn’t care about your circles. “

Andy Buckett said that we are committed to analyzing information about people to help buyers and sellers conduct transactions. They track user interaction data on websites and advertisements, adjust advertisements based on these data, and then collect other relevant information such as people’s preference for houses, budgets, and when to make buying and selling decisions. He said that generally speaking, people who get a pre-approval for loans have big interests in house buying. At the same time, sellers who need cleaning services really want to sell their houses.

4 Big data: empower the process of house buying

Unlike Rex’s people-oriented data analysis, the Localize. city website operating is dedicated to data analysis centered on houses.

The company combines public service data and real estate data to provide more information about the house, including noise, future development prospects in the surrounding area, and even the safety factor of the nearest intersection.

Company President Steven Carifowitz said: “A large number of surveys show that 40% of US buyers feel regret after buying a house for two years.” This is because they found that what they value most when buying a house changed a lot two years later. 

For example, someone wants to buy a four-bedroom penthouse in SOHO, New York. The price of this apartment is 14.5 million US dollars. The advertisement says that this apartment can enjoy 10 hours of sunshine in summer, which is four hours longer than the average sunshine time of other Manhattan houses. However, the local city network will provide information that since this district has approved many building permits, the future sunshine time and landscape will be very different. Big data will provide true information to clients.

The rise of big data has brought many challenges to the traditional real estate industry. In fact, a lot of data was generated before every link in the real estate industry, but many of them were ignored. For real estate companies, the first step is to collect the most valuable data to generate valuable information and provide support for decision-making. After data collection, the next challenge for real estate companies is to interpret the data. Currently, the real estate industry faces a “data divide”, that is, the ability to use data is far behind the amount of available data. For many real estate companies, solutions can be found through cooperation between companies specializing in data analysis. IDEAMAKE – The common choice of China’s top 100 developers, is building a new digital ecology of the real estate industry, and help more real estate companies digitally upgrade! What’s your opinions about the topic, If you have any questions about the article or want to discuss with us, please leave us a comment below or email us:


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