The use of Artificial Intelligence is steadily making its way into the real estate sector in an increasingly incisive and aggressive manner. There are even those in the industry who speak openly of a future revolution in this sector by these new technologies.
Through the use of Machine Learning, applied above all to Big Data and IoT, it is possible to streamline and modernize many aspects of real estate; from the collection and management of data derived from the sale, to the maintenance of the property itself.
There are so many examples that can be cited here, some already widespread, and the technologies and methodologies that are believed to become commonly used in the near future, could be, but not limited to:
–Data acquisition for marketing purposes: the huge amount of data belonging to consumers, collected through applications enabled with artificial intelligence, can be used to create lead generation and content marketing campaigns more effective. In addition, the real-time analysis of the data makes consumer preferences known and allows one to send hyper-targeted proposals, which take into account not only the key parameters selected directly by the potential customer, but also those derived from their consumer experience.
-Systems for both the collection and automatic filling of documents: artificial intelligence can be used to automate the filling of reports useful for customer management in terms of CRM. In addition, through NLP (Natural Language Processing) documents can be scanned to identify inaccuracies and inconsistencies, reducing the risk of human error in manually entering data.
-Evaluation of the propensity to buy/sell: Machine Learning can be used to analyze the historical data regarding the potential customer’s income, allowing to evaluate the actual economic capacity of visitors in order to discard those who have no real intention or possibility to purchase a home or business space. Through the screening of income data, it is also possible to carry out an assessment of creditworthiness and automate the process of guaranteeing commercial mortgages. Similarly, the machine learning algorithm can evaluate the probability that the sale will take place, analyzing the seller’s income, the events in his life that may affect the sale, his/her behaviour, etc…
-Predictive analysis of the real estate market: according to the Real Estate Evaluation Code, “the market value is the estimated amount at which the property would be sold on the evaluation date between a buyer and a seller, both being unaffected by external factors and after adequate marketing activity from both sides”.
Whether it is a commercial space or an actual house to live in, the estimate of the property value is influenced by many factors; reference is made to the data present in public registers, to the indices of the IMO (Observatory of the Real Estate Market), to the presence of adequate school and transport services, to the crime rate, to the existence of green areas, to pollution, etc… It should be noted that some of these properties with thousands of data points are certainly not within the reach of simple “human” analysis, and as such they can therefore be fed into an AI algorithm to carry out a current estimate of a given market, and also provide a robust predictive analysis of these parameters (i.e. the so-called Long Term Value).
There are already applications out there that can provide a potential customer with information regarding, for example, the number of hours of sunlight present on a property in a given period of time, reviews of schools and local services, entertainment venues offered or in the process of opening, the parking areas etc…
The estimate of the property value can be made, not only for the benefit of sellers/buyers, but also for the banking institutions. Before granting a mortgage or loan, in fact, the bank has every interest in knowing the value that the property will have on the market (in particular that of auctions) in the long term, to understand the actual value of the mortgage, should it be put back on the market for enforcement of the credit guarantee or foreclosure.
–Property maintenance prediction: real estate companies can easily keep track of the maintenance activities carried out on the properties for sale or for rent, in their portfolio. By monitoring this data, with the use of AI software, it is possible to identify the most common maintenance problems and fluctuations in the prices related to either area and/or season.
–Mortgage fraud detection and prediction: all those situations in which false information is presented to the credit institution in order to obtain a mortgage or loan, for which the requirements are not actually met, are included in the case of mortgage fraud. Machine learning models, with their ability to screen large data streams, can help to detect and anticipate all those situations in which documents are falsified and artificial pretexts are presented for obtaining a loan.
-Use of chatbots in sales assistance: some real estate agencies are already using the help of chatbots in the management of activities related to the sale/rental of properties. Chatbots can, in fact, be used as real virtual assistants able to record appointments for visits, to answer questions about the characteristics of the properties, to ask questions in turn to correctly profile customers and screen for real potential clients, etc…
The examples cited so far represent only a glimpse of the vast possibilities represented by the potential use of these, and other technologies which, should be considered an aid and not a substitute for the human component.
Author: Claudia Paniconi | Marketing Manager at DMBI