How AI technology has changed the real estate industry

Like most sectors globally, the traditional industry of real estate is steadily adapting to technological changes. Nowadays, artificial intelligence (AI) isn’t just a buzzword, but a revolutionary piece of technology that applies to many aspects of the industry.

Luckily, advanced technology is no longer out of reach and can be easily accessible to agents and agencies aiming to maximize their portfolios. Most notably, it is transforming the way people buy, sell, and rent real estate. In this article, we list out 3 ways AI technology has changed the real estate sector.
 

1. Gives recommendations on properties based on client preferences

When it comes to prospecting and finding the right listings for your clients, the process can be tedious and effortful. Understanding your client’s needs requires attention to detail and noting down their every requirement. From location preference, property size, the number of bedrooms, required amenities, price sensitivity – the list goes on.

Needless to say, gathering all information and going through rows of potential listings to find a good match can be very time-consuming. If only there were software that could help you match clients with properties with the perfect listing…

When you integrate your CRM and listing website, AI algorithms can accumulate data in real-time and generate recommendations based on customer preferences. It combines attributes like past purchases, search filters, interest in specific property types, and other notes that you may have marked down in the CRM to generate calculations.

AI can help agents identify properties most suited for each client and provide high confidence search listings, matching results, and recommendations. Whether you are a client or agent, this helps speed up the property-hunting process for both parties.

Property Raptor’s agent management tool does exactly that. Using advanced predictive algorithms and machine learning, Raptor analyzes existing client data to match relevant properties. Since machine learning algorithms process data without predetermined rules, it continues to learn to process more data. Raptor can identify otherwise overlooked attributes and draw comparisons between seemingly unrelated attributes and pull in listings that share similarities.

Raptor’s AI-matching works both ways. Agents can identify properties for clients, or on the flip side, match clients with a particular listing you wish to sell.
 

2. Converts and manages leads with chatbots

An agent’s time is extremely precious, but with tons of traffic coming into a website or social page, they need to focus on managing lead inquiries purposefully. It can help save hours with AI-led chatbots as it automatically conducts a preliminary lead screening to filter out the qualified ones. Chatbots can also help answer inquiries, such as price range and location preferences, giving agents a wealth of data before reaching out.

We know that social media helps generate leads, and targeting potential clients through ads is a popular channel used to grab audience attention. If you are using Facebook to launch ads, connecting your business account with Facebook Messenger’s Chatbot can help you save time identifying leads and managing communication.

Once a user clicks on your Facebook ad, a Messenger chat window with a chatbot will be ready to answer inquiries. This functionality allows agents to manage leads without wasting time on unqualified contacts, go on autopilot with 24/7 availability, boost engagement, and ultimately increase the chances of closing deals.
 

3. Predicts property valuation

One of the significant features of AI is its ability to help predict the future, particularly for assessing property value. Property valuation has always been complex due to the sheer volume of market data points and the industry’s ever-changing landscape.

AI’s ability to analyze vast amounts of data and identify trends and patterns in real-time can be instrumental in making predictions about the housing market. It can carry out rounds of automated analysis using self-learning models, where human analysis and traditional market research were not capable of conducting.

Skyline AI collects data from various sources and uses AI to analyze transaction data. This helps to provide insights on which neighborhoods are growing in popularity or heading for a potential downturn. It may aggregate data about public records, transportation options, crime rates in the area, and school district ratings to generate an analysis of a particular property’s value.

Similarly, Enodo helps clients predict optimal market rents, operating expenses, and identify investment opportunities by extracting rental revenue, lease turnover, and other historical and real-time data. This data is essential when agents need to advise investors on decide which properties to add to their portfolio.

AI has made spectacular progress in the real estate market by helping agents and managers obtain greater insights and save valuable time. As AI and machine learning get smarter by the day, including them in your business processes will be beneficial, and eventually, essential. If you are looking to implement your own AI strategy in your real estate business, CONTACT US today!