Real Estate and E-commerce

Big Data brings predictive management to the heart of the real estate professions. Predictive investment models are particularly in the spotlight. They will develop even more over the next few months and years.

 

Access to analyzed data allows real estate agents and other professionals in the field to refine the targeting of their clients via visualization tools, but above all to set up, for the most advanced algorithms, predictive analysis to anticipate the future needs of their customers.

 

Data science is pursuing its revolution in the collection and use of data in all sectors. Real estate and E-commerce are not forgotten in this perpetual movement. Thanks to related technologies, they thus have the possibility of acquiring more easily and more quickly knowledge on the market and on the behavior of buyers, sellers, tenants or simple prospects. And that's not all, predictive analytics opens the door to all possibilities.

Real estate and e-commerce are no exception to the rule: they produce an impressive stream of continuous data that should be analyzed. These data mainly relate to:

 

• Price changes.

 

• The deadlines linked to the various transactions.

 

• Information on past, current and future projects.

 

• The number of real estate transactions.

 

Data pertaining to the customers are:

 

• Rental investment projects.

 

• Principal residence purchase projects.

 

• Information relating to mortgage loan applications.

 

• The level of household debt.

 

Thanks to Data science tools, businesses can thus collect this data, combine it and analyze it for the purpose of anticipation. The correlation of information makes it possible to anticipate the needs of a buyer or a seller.

 

Many tools related to Big Data have thus developed to meet the needs of real estate and e-commerce businesses. We are thinking in particular of CRM to collect information but also of data visualization to have a global vision of the market and adapt its development, growth and marketing strategy. Sites currently make it possible to estimate changes in the short, medium and long term, to sell a home in a few minutes or to find potential buyers interested in a specific property. A considerable saving of time for the real estate professions.

Real estate market data (number of transactions, average time, price trends, etc.)

 

Data specific to buyers (socio-professional activity, income and budget, home-work journey, community affinity, budget, criteria for the property sought)  

 

Data related to the environment (infrastructure and public equipment, shops)

 

Data dealing with the sales process (number of ads viewed, average time between first contact and signing of the deed of sale)

• Target clients: Big Data tools allow real estate agents to know which property may be of interest to which target. They therefore avoid wasting time in any unnecessary prospecting.

 

• Anticipate customer needs: having all the information and data on an asset and on a sector makes it possible to anticipate needs but also customer requests and objections. The real estate professions can thus arrive with a solid file to convince and persuade. With the analysis of real estate projects in progress in a more or less large sector (district, city, district, regional department, etc.) real estate agents make supply and demand coincide.

 

• Help clients in their choice: if human can never be replaced in real estate and e-commerce, Big Data brings real added value to the sale and purchase process. Accurate information in support, the real estate agent can thus bring his know-how to his clients. Location of the property, nearby services, direct environment, amenities and so much data that the professional can relay to individuals in a few seconds. These are obviously decisive criteria in the purchase decision. Disseminating them transparently and quickly is a real plus to help the prospect take the plunge.

• RealData.

• Zilculator.

• RealNex

• Dealcheck

• Buildium