Big Data in the real estate sector: How does it affect users?

Big Data, artificial intelligence, Machine Learning, or proptech tools are some of the technologies that allow optimizing, streamlining, and providing transparency to the process of searching, renting, or buying and selling flats and houses, and that is why they are increasingly widespread in the real estate sector.

In the case of Big Data, we are talking about the possibility of having tools to store, organize and compare the large amount of information related to real estate that we continuously generate in sources such as web pages, search engines, Smartphone applications, or social networks.

This includes sale offers, but also real estate promotions, forecasts of variations in the market, trends, investment possibilities, etc.

This data is continually growing, making it difficult to manage and, above all, analyze it. What Big Data tools applied to the real estate sector do, precisely, is collect them in blocks and analyze them. The final objective is that they become tangible, practical, and concrete information that helps to assess all the available options to make the best investment or purchase decisions.

One of the great advantages of Big Data applied to the real estate sector is the possibility of identifying new opportunities and market strategies, more efficiently. This is not only positive for real estate agencies like Replace, but also for companies, investors, and, of course, individuals who want to buy or sell a flat or a house.

5 benefits of Big Data applied to the real estate market

Among the main benefits of Big Data applied to the real estate sector, we highlight five:

Lower financial risk and higher profitability in real estate operations

Going ahead and knowing what type of properties are the most requested and in which areas, avoids (or at least considerably reduces) some mistakes made in the past, something important in a sector such as real estate, especially reviled after the 2008 crisis.

Thanks to Big Data, buyers can anticipate changes and crises, mitigate their effects or reorient their investment strategies using real, objective, and permanently updated data.

Reduction of uncertainty

Using Big Data correctly reduces uncertainty. Crossing data of current real estate assets with records of previous apartments, it is possible to mark an evolution of the real estate market and its trends that can be very useful.

In addition, conducting a geolocated study of a property allows us to analyze a neighborhood or an entire town to know if it has enough green areas or parking spaces, what is the traffic density, if it is advisable to build new commercial premises or if it is well located to assume a new office building. This is positive both for investing and for knowing to whom we can sell an apartment or a house.

 More transparency and reliability

Big Data analyzes objective data. The companies in the sector can compare, know and establish fair prices for the properties they manage based on parameters such as their age, their characteristics, the level of security, or the average costs of other similar properties in the same town or area. Only then will the buyer receive his ideal apartment, that is, one that meets his requirements and that fits his budget.

 Save time and money

Thanks to Big Data, buyers have more information to decide which floor interests them the most. Potentially, the final decision will always be faster and more accurate, saving time and money than this means for all parties involved in the sale. 

Big Data also facilitates and gives security to operations such as the exchange of documents, the request for certificates, economic transactions, etc.

Greater professionalization of the sector

The use of Big Data in the real estate sector allows professionals to offer their clients a quality service since they have transparent information that increases the relationship of trust between agents and buyers.

Big Data also plays a prominent role in digital marketing strategies. Thanks to this technology, we can know which client profile enters our site (through the search engine or the real estate social networks) and create a stable network of contacts to turn each visit into a potential client. 

Can Big Data help you buy or sell a house?

Of course! The use of Big Data in the real estate sector reveals the behavior of potential buyers so that real estate companies can prepare personalized offers for each user.

For example, if you are thinking of selling your house, thanks to Big Data, we can automatically evaluate your home. In this way, you will know what its current market value is from the cadastral reference, the location, and other similar offers in the area.

These data, in turn, can be combined with others, such as the demographic and socioeconomic information of a neighborhood, the evolution of the prices per square meter of the properties sold in the last year, the type of households (if the majority are flats in blocks, developments or single-family homes) or the stock of homes for sale.

If what you want is to buy, Big Data can also help you. Basically, these tools gather the information and data on available housing prices based on your needs or preferences (price, dimensions, number of rooms, area, state of the facilities, etc.).

Thanks to this technology, you can even know if the price they ask for a house is in line with its market value, or if it is a good time to buy in other areas that are going to appreciate. In fact, one of the main uses of Big Data in the real estate sector is precisely to detect and anticipate market trends.

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On the other hand, Big Data can help you obtain financing to buy a house or, at least, to know what options you have at your fingertips. The data support this: in the last year alone, three out of four people who decided to buy a home consulted online "calculators" to get an idea of the amount of money they should finance, the type of loan that most interested them (with variable, fixed or mixed interest) or what your monthly payments would be.

This information is very useful for buyers who want to buy a home and for professionals in the real estate sector. Also for banks and finance companies. The latter can know the economic data of those who are requesting a loan to buy a house and what their behavior has been in the past in this regard in real-time. This is something basic to offer some financing conditions or others, more quickly, speeding up the purchase process.

→ It may interest you: How to sell my house in the digital age

The real estate sector faces increasingly demanding clients. Digital transformation makes things easier, although "conversion" is being slow and expensive. However, the results are worth it: using tools based on Big Data technology, real estate agencies like Replace can offer much more personalized services to our clients, who get much more transparency when buying a home.