What are the Use Cases of Big Data in Real Estate?

Big Data Analytics in Real Estate

Catching up on big data & real estate

Real estate is comprised of assets such as property, land, houses, and buildings. Real estate is a budding sector where properties are dealt with every now and then. Real estate agents facilitate the buying and selling of homes, land, etc. on the behalf of the parties whose interests are vested in it.

Big data is a common term that is widely accepted for large sets of data which is analyzed using various computer software to bring out trends and other insights to understand consumer behavior and several other aspects of the economy.

How is big data related to real estate?

Big data has transformed the way data is perceived these days. It has facilitated a smooth analysis of data and the extraction of vital information. Real estate involves a huge client base thus involving a huge amount of data. There are buyers, sellers, financial institutions and a lot of other parties who require data chunks to cater to their specialization.

Real estate is moving to an electronic mode thus becoming more data-centric. People are buying and selling properties using mobile platforms thus collecting huge amounts of data. The real estate agents through these application data can easily get to know about the properties which are in huge demand and thus control the rates of the already volatile market.

Real estate should have hands-on big data so that they can reap out the benefits of the huge data resource available. Buyers are moving to a mobile platform where they can assess various property options at the same time and improve their search experience. Realtors will also know their clients better and serve them in accordance with their needs. This data is really valuable.

The biggest challenge in the real estate industry is that technology touches this sector at a very slow pace but the roots of technology are growing so fast that the real estate sector has also got a good taste of it.

Influence of big data in the real estate sector

Big data plays a real role in fixing the prices of tangible properties. Also, people who have an intention to buy get to know about the prevailing market rates. The realtors can analyze the cash flows which can take place in the future on the basis of demand. When an interested party visits a real estate website he knows what he is searching for. He has his specific parameters in place thus giving the app controller user-specific data.

The big data analytics training the realtors with a lot of information about an individual such as his age, region to which he belongs, what kind of house does he require, etc.

Such information helps the realtors to make notifications and emails more personalized thus winning the trust of the consumers. Big data also gives an insight into people who are interested in taking properties on rent. These real estate giants have access to a database of millions of people.

With the help of big data, real estate companies are able to market their products efficiently and smartly. Big data is being used by the realtors in marketing their products and also reaching their prospective clients with the help of various marketing campaigns such as email marketing, influencer marketing, celebrity marketing, etc.

Big data also helps in improving the decision-making process for these companies and also for the individuals who are visiting the application. With a plethora of options available, an individual could get all sorts of information on a particular house such as the locality it is in, how old the property is, how far the market is and so on.


This shift in the outlook of real estate businesses has just begun. The more these companies analyze the data available, the more it becomes lucrative. The process of implementation of big data in the dynamics of real estate business is a little slow but all good things take time. Also, they have already started to make the best out of the data available by slowly unwinding the treasures hidden in the layers of the so-called complex data.

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