Big data is revolutionizing the collection and use of data in the real estate sector. Thanks to big data, real estate professionals have a better understanding of the market and the behaviour of prospects. But big data doesn’t stop there, it goes even further with predictive analytics.
Big data in the service of real estate
Like other sectorsReal estate generates a significant amount of data on an ongoing basis.
Real estate market data
Information in the real estate sector comes from different sources. Thanks to the big data, data relating to the real estate market has become easily accessible:
- Evolution of market prices
- Average time to complete a real estate transaction
- Building projects
- Number of real estate transactions…
This data can also be linked to customers:
- Household composition
- Real estate investment projects
- Real estate loan
- Debt level…
Some data are also related to the environment:
- Number of shops, schools
- Number of public transport
- Age category
- Unemployment rate…
The tools of the big data
Thanks to various tools, real estate professionals can collect this data and cross-reference it in order to anticipate a buyer’s needs. While CRMs facilitate data collection, dataviewing tools make it possible to better visualize them so that strategic decisions can be made.
Websites can nowadays estimate future market price developments. Other platforms offer the possibility for owners to sell their property in one minute. Still others offer real estate professionals the list of prospects most inclined to sell.
Impact of big data for real estate professionals
For real estate professionals and startups alike, big data is a real mine of information. The analysis of the available data not only allows to refine the targeting of customers, but also to anticipate their specific needs.
The big data, a decision support tool
Big data is not going to replace the profession of real estate professionals, since human qualities cannot be replaced by digital. On the other hand, it assists in decision-making and allows them to bring added value to their business.
Today’s real estate professionals have easy access to a variety of data on location and environment, determining criteria for whether or not to complete a transaction. And to make predictions, they rely on numerical market data and owner data.
Application of big data in real estate
Thanks to predictive analytics, the data collected can now be used to anticipate the behaviour of prospects and to propose offers adapted to their needs.
Concretely, le big data can help real estate professionals to find the property best suited to their client’s needs.. By analysing current real estate projects, they can identify potential buyers in this sector in advance.
Big data in commercial real estate
Big data has become a real issue for real estate professionals. They need to take advantage of the megadata available. They can then rely on different algorithms to optimize the management of customer data, ads, their property portfolio, etc…
Digitization of management processes
SCPI management companies (non-trading real estate investment trusts) like Voisin have already understood the importance of big data and digital transformation. As they move towards digitalisation, they now rely on big data to carry out the analysis, valuation and forecasting of buildings.
In particular, the management company Voisin has formed a partnership with Pricehubble, a start-up company specialising in data analysis and valuation for real estate. It now integrates the algorithms developed by Pricehubble into its investment process. In concrete terms, the tool will enable the management company to analyse the performance of each asset according to several criteria and thus refine its real estate strategies.
Towards predictive management
Big data also places the real estate business in the era of predictive management and predictive investment models will be developed. Many real estate professionals are currently using big data-based tools to analyse market dynamics and urban developments.
Thanks to these numerical tools, it is possible to synthesize the data that the investor needs to determine the ideal location of his building: the sector, existing and future infrastructures, services, size of the park… These tools also make it possible to identify the most interesting investment opportunities by anticipating the evolution of the rental and market values of the properties on the market.