“Data Mining for Real Estate Agency”, Hervé Parent PBA – Property Business Accelerator

The data available through open data is a goldmine for professionals who know how to use it.

The digitization of the economy has generated massive amounts of information about people, their behaviour, their goods, their exchanges, their values…this is called big data. At the same time, the open data policy has made many databases reserved for management accessible to all.

Data mining is a group of techniques that allow the exploitation of databases and big data. Data mining is an Anglo-Saxon term that can be translated as “data exploration” or “extracting knowledge from data”. Concretely, it is a set of automated or semi-automated tools that allow the analysis of a large amount of data. The goal is to find correlations, anticipate trends, and make decisions based on reliable information. William Violet of Homiwoo explains that data mining is above all a decision-making tool. This was confirmed by Ludovic Gauvin, Director of Data at Yanport, whose job is to structure data and build relevant tools to help real estate professionals make decisions.

Real estate is particularly concerned

Current data useful for real estate professionals relates to properties, prices, advertisements, people, territories… For people, we can find out their gender, age, social and occupational group, as well as their behavior in particular on the Internet and on the Internet. social networks. All these databases respond well to definitions of big data, they are very large, and data mining is necessary because exploiting them requires complex tools. The number of interesting rules for real estate is increasing: “Over the past three years, we have had more and more clarity about transactions,” says Peric Brito, CEO of Le Prospecteur.

Learn about values, research mandates, and conduct market studies

Concrete applications for real estate can be grouped according to three general functions: knowing values, researching mandates, and conducting market studies.

Knowing the values, selling prices or rents makes it possible to make assessments more reliable, but also to provide online estimates in order to determine which owners have a real estate project. Authorizations are sought, as well as online estimates to generate leads, through online behavior analysis or behavioral databases. Obviously, doing market research allows you to know your area to better serve your customers, but also to publish rich, relevant and updated content on a website, blog or on social networks.

The databases used are kept confidential by the companies that run them, they are part of their business. But they all analyze the DVF, Insee, Data.gouv.fr and ads. Some of them have agreements with banks and insurance companies to be able to use their files. For William Violet of Homiwoo, there are three main use cases: capturing leads, professionalizing value insights and implementing market observatories for SEO. For Ludovic Gauvin from Yanport, in the future we will also be able to use the technical data of the building, for example BIM, in order to improve assessments and we will have advanced indicators through data analysis from Google Trend.

The analysis methods are very complex and the teams include high-level engineers and mathematicians. One company has partnered with École polytechnique to develop its own analysis methods. The complexity comes from the fact that data is only interesting if crossed with other data. Pierrick Pretot describes data mining as follows: “Data is retrieved by bots, APIs or in open data, then stored on dedicated servers, then processed to be readable and finally crossed with other data to speak.” The miner retrieves more than a hundred events or signals that are precursors or lead to transactions.

Very fast growing startups

The companies that offer data mining to real estate professionals are startups, with one exception. They are rapidly evolving and changing their service offerings to be more precise and to better meet the needs of real estate agencies.

Data mining startups

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