“How AI and ML are helping Real Estate Industry through algorithms that are capable to process the data at a room-by-room level.”
Artificial intelligence has become the breakout technology in the past decade. By harnessing copious amounts of computing power to learn and identify patterns in data without human intervention. These algorithms can be used for nearly any problem or question, provided there is enough input data for the algorithm to process to generate realistic predictions. These use case scenarios mean that industries that have traditionally relied on purely human-driven research and development can now harness massive amounts of data to become more efficient and more profitable.
A core sector undergoing this technological shift in recent years is the real estate industry. Property ownership has always been driven by personal preferences and human interactions among buyers, sellers, and real estate agents. But now, with algorithms capable to process individual preferences and generate data at a room-by-room level, massive changes to the buyer-agent-seller paradigm are happening.
Let’s dive into know-how AI and ML is helping Real Estate Industry
AI and ML in The Real Estate Industry
One man who has influenced the real estate industry’s technological revolution is SetSchedule’s CEO and founder Roy Dekel. SetSchedule has developed a multi-patented agnostic leads marketplace featuring leads from top tier real estate publishers and lead generation websites. The marketplace alongside a multi SAAS products suite, leverages AI-powered predictive analytics, big data and machine learning technologies to deliver better business efficiency to agents, teams, brokers and industry verticals. Additionally, before founding SetSchedule, Roy led a high-profile investment fund that used to buy houses the traditional way.
During his time as a leader of that investment fund, Roy learned some key lessons on the efficiency of the traditional real estate market. According to Roy, “curating leads, identifying customers, rigorous follow-up,” and a plethora of other tasks related to linking potential buyers with current sellers was “extremely daunting.” The enormous amount of energy and time spent on a single property sale seemed quite inefficient and exhaustive.
How AI and ML is helping Real Estate Industry – Home Value Appraisal
With this in mind, Roy identified some key areas where technology could influence the space – and in particular, areas where AI and machine learning could significantly disrupt tradition. One key area where AI is already influencing the market is in home value appraisal (also referred to as comparative market analysis, or CMA). When a person approaches a real estate broker, the broker will analyze key data points to appraise the deal. Location of schools, shops, and other homes, as well as square footage, in-home upgrades, and more, are deciding factors.
Unfortunately, data analysts had a limitation to process only a few factors in a realistic amount of time. But ML algorithms can compile huge amounts of data, process all of it to find patterns in home value, then return highly accurate valuations for homes in a relatively short period. Factors like neighbor volume, number of cars passing through, and even vegetation on lawns can be used in these algorithms. This is one of the key uses for machine learning, stating that “machine learning software can analyze all the factors. Significantly increasing the accuracy of an agent’s analytics”. An agent can use these tools to augment information during the sale process.
How AI and ML is helping Real Estate Industry – Finding the Right Buyers
Another aspect of the real estate industry that’s using AI is the targeted advertising space. While targeted advertisements have been part of Google and Facebook’s wheelhouse for years. Other industries have found it difficult to link buyers and sellers without hands-on time from experts in the space. In real estate, this is especially true – the exhaustive lead generation and customer chasing is the industry standard for advertising.
Fortunately, recognizing patterns in individual-level data to find potential homebuyers is a fantastic use of deep learning algorithms. These algorithms can be utilized in places where homebuyers are likely to search for homes (and in some cases, on social media platforms like Twitter and Facebook), scanning for buyer profiles that match homes on the market. By identifying willing buyers, algorithms can highlight potential buyers.
This is the principle behind SetSchedule’s Smartmatch software. It scans all the data generated by thousands of agents to understand which leads resulted in successful home purchases. Other services like Coldwell Banker’s CBx app have also adopted this technique. This signals a massive shift in the way that agents and homebuyers seek each other out for upcoming deals. According to Roy, these artificial intelligence-driven apps will be critical in “assisting brokers, teams, and individual agents to find clients.”. But they won’t replace the human touch of the real estate industry anytime soon.
Technology is critical to most aspects of everyday life. And industries that rely on human interactions still are feeling the impacts of technology. The applications of algorithms used in machine learning are technological tools for sectors like real estate. Through machine learning, real estate agents can amp up the efficiency and productivity of their sales pipelines.