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Real Estate
How the Use of AI Can Add Value to Your Real Estate Business
May 8, 2020
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Adapting to a ‘data-driven’ world is essential for modern businesses to survive, and thereby, increasing the use of artificial intelligence techniques and attributes in several business processes. With AI integrating itself in many business sectors in today’s economy, real estate businesses are no stranger to integrating machine learning and data analytics solutions in their business practices.

Here’s How AI is Helping Real Estate Businesses Thrive

Adapting AI models to different tasks has added value to several real estate businesses. Here’s a look at some of the ways AI is helping real estate businesses thrive.

Improving Lead Generation, Marketing and Customer Recommendations

Consumer end apps with AI-empowered marketing and chatbots are already helping businesses understand customer requirements and allow for content adaptative marketing. Through these processes, it is possible to generate new leads. That once was an embedded chatbot on your website or application which communicated with your customer, it is now possible to create personalized content for that particular customer and turn them into leads for future investments and deals.

With the power of a smart chatbot, it’s possible to customize content for the customer and provide answers to common queries straight from the ad clicks,such as what kind of properties the business is affiliated with, the price range of properties and areas where the business holds most properties.

Finally, with a self-learning intelligence embedded on the listings page of the business, AI has been used to generate curated recommendations for properties based on purchase history, and specific property views.

Predicting Property Market Values

When it comes to predicting and analyzing housing prices, machine learning has been used quite frequently in past studies and has become the first topic when teaching new students about machine learning. That is, predicting housing prices based on region, housing square footage, number of bathrooms, number of balconies, etc. Using this information, it is possible to predict the optimal housing prices of a new property in a location and fetch the best possible price for that particular property.

Thousands of other variablessimilar to those mentioned above, such as property characteristics, crime rates, schools, and other buying trends have helped businesses aggregate all this useful information into great property values with larger margins and ROI. Given the massive amounts of data, a human can’tperform such an analysis and therefore,we can leave it to the machine to decide what the best value of the property would be, given some criteria. Currently, players in the market such as Skyline AI and Hiltch have been offering market value prediction services to empower real estate investors and turn investments into huge success stories.

The Future of AI in Real Estate Shows A Lot of Promise

We’ve talked about just a few of the many ways AI has added value to prime real estate businesses and shows; allowing for further growth through extensive research, implementation, and expansion. While it can be assumed that many state-of-the-art algorithms are already being developed, there is room for future real estate business owners to make AI a core part of their business process and take a data-driven approach to further enhance their customer-facing value chains.

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Richard Nevis

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