Now it’s possible to find a property in few minutes, know all about its surrounding area or what the price of an apartment will be in a year: big data transforms the real estate sector. Both real estate agencies and clients benefit from new services.
When looking for a house, our expectations are often the same: to quickly get complete and detailed information about the area that appeals us. Fortunately, start-ups are taking note of what customers want and are offering innovative B2C services. In United States, Opendoor relies on its ability to generate fair price offer for any property within ‘one minute’. Similarly, Zillow predicts what a home value index will be one year from now, a service that covers entire North America. In France, Noam helps people of Montpellier find apartments, houses or commercial spaces that suit their description and requirement in terms of transport, market area and other services. Transparency is also taken care of with platforms such as Rentswatch, which allows comparing rents in Europe.
In B2B segment also, we are seeing new innovations. These include SmartZip, which analyzes data on age, end date of mortgage, family situation, etc and allows real estate agencies to identify the top 20% of homeowners which are most likely to turn into customers in an area. Thus, we now have intermediaries between users and real estate professionals. The data scientists and developers of MeilleursAgents.com offer along with purchase, sale and rental services, interactive maps of French metropolitan areas. These maps link rents and prices per square meter near public transport stations to help choose a new place of accommodation.
What would be the product that can make a difference in this sector? It should improve the quality of life index in an area. It should connect the information on the market and neighborhood of the area sought as well as the content published by its inhabitants. Who would not dream of being able to get reviews of restaurants, schools and doctors in neighborhood on a single click? The output should not just show an ultra customized selection of goods for potential buyer but also give a dose subjectivity, which algorithms cannot provide. Which actor will find the magic formula to improve this index?
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