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04 April 2019

Why Real Estate Needs to Step Up Its AI Game

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Even though AI has become a buzzword in many sectors, it hasn’t replaced jobs as many people feared. For example, we haven’t seen real estate agents substituted by computers so far, and we can safely bet that it is not going to happen in the next decade. Instead, there is a rising trend to use AI to get competitive advantages on this market that is becoming ever more crowded.

Why AI for real estate?

AI has the potential to bring many significant changes to decision-making and the overall efficiency of real estate operations. This is possible as AI generates additional insight from pattern recognition, an area which was inaccessible to ordinary real estate agents but is customary to AI algorithms.

As PwC highlights, there are several categories of AI tools which can be useful on the real estate market, ranging from automating tasks to taking independent decisions.

The first level deals with automating routine (and sometimes non that routine tasks), like assigning neighborhoods based on coordinates or addresses. The next level is the so-called supporting intelligence that is about assisting human-led processes, making them more time-efficient and accurate. As a result, this can help to respectively expand the knowledge directly related to the quality of decision made. Here, we can speak about such tasks as evaluating price fluctuations, the likelihood of a property to be on the market for longer, or identifying good investments. The last level is called autonomous intelligence and requires no human intervention. This is the area of chatbots and automated customer support tools.

Real-world applications of AI in real estate

Still in its infancy, AI for real estate has been adopted by pioneering companies. It is successfully used in various forms, ranging from recommendation engines embedded in websites to helping venture capitalists find their next portfolio piece. AI-based customer care is also on the rise as chatbots become more popular and smarter. Here are a few of the most relevant and innovative uses for this new technology.

Recommendation engines

In a similar way to Amazon’s recommendation strategies, AI solutions can help other verticals to increase the relevance of their offers. This is done by creating tailor-made sets of items based on a client’s preferences and previous interactions. For first-time customers, the system can use profiling techniques and present them with more generic findings which worked well for similar past clients.

AI could help optimize real state databases and provide recomendations. Image: Unsplash

Implementing this is necessary because searching real estate databases is becoming long and tedious. A smart system that could help to find just the right offers for the client’s budget and interests could quickly become the preferred search method.

Market analysis

There are a few tech companies offering AI-based tools to anticipate market fluctuations and offer investors potentially hot properties. For example, Skyline is one such company promising to serve as an investment manager and provide the combination of human know-how and AI capabilities to predict future sell and rent prices, identify market trends and pinpoint opportunities.

Since the real estate market is also about perfect timing, such tools should also provide insights about the best moments to renovate or sell a property.

Chatbots for customer care

The hectic life and work schedules of some people demand that real estate companies adjust their working hours and client care models. Since it would be too costly to have a 24/7 call center, an economically viable solution is to develop a chatbot.

The current advancements in natural language processing and machine learning mean that some bots can even pass the Turing test, which means that they are perceived as humans, not a machine, by other humans. In an experiment conducted in 2016, a bot was put in a head-to-head race with a real estate broker to find the perfect home in the Denver area based on a potential client’s initial input. Every day the client received six proposals, half from the bot and half from a seasoned agent — and every time the bot’s list was preferred.

If we take into consideration that once setup they don’t require an additional salary and they become smarter as time passes, real estate agents may have serious competition here.

AI solutions could save most of the time agents invest in customer care. Image: Unsplash

Targeted advertising

In the previous example, we’ve learned that a chatbot can provide excellent client service, even better than a real broker, but can AI be useful in attracting clients?

The simple answer is yes, and it can also surpass humans by carefully studying behavioral patterns and preferences. One company which does exactly this is REX real estate. They only charge 2% of the price for both sides, thus staying on the lower end of the commission spectrum. and the company offers both dynamic pricing services as well as customized client targeting on the most popular platforms, including Zillow, Facebook and more. The prominent feature of this service is that it can have a high closing rate by shooting its advertising to those who are most likely to be receptive.

Smart contracts

This term is usually used in connection with blockchain, yet it covers a broader range of applications. It stands for a digital deal that has been appropriately tagged so that its information can be easily retrieved and reused with minimal redundancy. This can reduce waiting times, mortgage approval times and more. Here, AI can act as a personal assistant and help clients complete their applications if the information in the existing database is not sufficient.

Final thoughts

As in other verticals, AI will not spell unemployment right away yet bring some inevitable changes to real estate businesses. It will be disruptive and cut off some practices, but it can also save a great deal of time and money when it comes to operational efficiency, client service and advertising.

The real estate market will become increasingly precise, and we can expect to see less buyer-side agents as most people who are computer-literate will be able to run their own search successfully.

Jasmine Morgan

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