Big Data in Real Estate: How Companies and Consumers Can Take Advantage Of It

At Plain Concepts, we believe that all industry sectors can take advantage of the power of Big Data, and real estate is no exception. Big Data in real estate represents a huge source of information for workers who sell, rent, or buy houses every day. Also, individuals who are looking for a new home for their life project and who, thanks to this technology, have an easier time finding it.

What is Real Estate Big Data?

Real estate big data is the collection, storage, processing, and analysis of big data related to the sector. As in other industries, it serves its workers to detect new business opportunities, anticipate future trends, and improve what is failing.

Big data and Real Estate

The relationship between Big Data and real estate sector can be analyzed from two points of view: from the workers in the sector and from the users who are looking for houses, offices…

Examples of Big Data in Real Estate

From the point of view of the companies in the sector, examples of what to use real estate big data for are the following:

• Knowing areas that are going to revalue. Movement, demographic, and geolocation data could be used to conclude where people move more and build new buildings there or buy them to invest in them.
• Anticipate possible economic, political, and security risks… Knowing the context of an area, and the environment in which its citizens move every day allows one to prepare for future dangers.
• Designing the internal layout of busy buildings: How should market stalls be laid out? Is there a space that can be better utilized in an airport, a bus station, or a shopping mall? Knowing how people move around inside them, new ones can be designed or fitted out.
• Designing marketing campaigns for building promotions, spaces in a shopping mall…
• Cross-reference the data of a building with a type of buyer (via CRM, for example). By linking the building’s data with a customer database, real estate employees know which of the latter would be more likely to buy it.
• Obtain reports on the financial capacity of buyers.

From the users’ point of view, there are also examples of real estate big data applications:

• Like employees, know the areas that will be revalued, in case they want to invest in them through purchases.
• Obtain a visual analysis of the reasons for buying or renting in an area: green spaces, public facilities… There is no need to scan a map: just cross-reference several data sources and select filters to obtain the information in an instant.

As a result, both parties spend less time doing the same tasks, and decisions are made more quickly.

Big Data in Real Estate Case Study at Plain Concepts: BBVA Valora View

At Plain Concepts we have worked with BBVA to help real estate clients get the most out of Big Data: BBVA Valora View is a mobile application to search for apartments using Augmented Reality, Big Data, Xamarin, and Artificial Intelligence, in order to create an x-ray of the area where we want to buy or rent.

The radiography was not only of the present moment but also a projection of the future: the application estimates how much a house may cost in a few years collects prices of surrounding properties… and with that information proposes a purchase price offer. It also calculates other possible costs to tell the user whether it is more convenient to buy or rent that property.

According to Gabriel González, Digital Product Manager at BBVA, the application was downloaded more than 8,000 times on the first day. In one year it achieved 80,000 downloads, with an average session time of 5 minutes.

As you can see, the application options for real estate Big Data are numerous and for various fields, and both companies and users obtain benefits. In addition, if combined with other technologies, such as Artificial Intelligence and Augmented Reality, more attractive applications are designed that allow greater analytical and business capacity.

At Plain Concepts, we know how to get the most out of real estate big data. We create a data storage platform for you or we provide you with an analytical solution and Machine Learning and Artificial Intelligence technologies.