Use Cases

AI for Real Estate Property Search

Explore how AI is reshaping the real estate property search landscape and the benefits it offers to both buyers and real estate professionals.
AI for Real Estate Property Search
Prompt: AI solution to search for real estate properties to buy --v 5 (Midjourney)
Table of Contents
In: Use Cases, Real Estate

AI is revolutionized many industries, with real estate being one of the notable sectors experiencing significant transformation. As technology progresses, AI's role in streamlining the real estate property search process becomes more prominent. In this blog, we will explore how AI is reshaping the real estate property search landscape and the benefits it offers to both buyers and real estate professionals.

Traditional property search methods often involve hours of manual labor, sorting through countless listings to find properties that meet specific criteria. AI, however, has changed the game by providing intelligent solutions that streamline this process. Here's how:

  1. Property Recommendations: One of the most impactful ways AI has transformed property searches is through personalized property recommendations. Using machine learning algorithms, AI can analyze a buyer's preferences and past search behavior to suggest properties that closely align with their requirements. This means less time spent scrolling through irrelevant listings and more time viewing properties that tick all the right boxes.
  2. Image Recognition: Another groundbreaking AI application in real estate is image recognition. AI can analyze property photos and extract valuable information such as the property's condition, the type of flooring, the presence of a swimming pool, and more. This additional data helps to filter properties more accurately based on visual characteristics, enhancing the search process.
  3. Predictive Analytics: AI's predictive analytics capabilities can forecast real estate market trends and property values based on a wide range of factors, including historical data, location, local amenities, and economic indicators. This allows buyers to make informed decisions and real estate professionals to provide better guidance to their clients.

Incorporating AI into the real estate property search process comes with a wealth of benefits for both buyers and real estate professionals.

Firstly, AI brings a new level of efficiency to property searches. It automates the search process and focuses on properties that precisely meet the buyer's criteria. This enhancement not only helps buyers find their ideal property more quickly but also supports real estate professionals in serving their clients more effectively.

Secondly, the accuracy offered by AI is another significant benefit. By analyzing large amounts of data and identifying patterns, AI can suggest properties that closely align with a buyer's preferences. This means that buyers are more likely to encounter properties that genuinely match their requirements, leading to a higher level of satisfaction.

Another noteworthy benefit of AI is its ability to aid in making informed decisions. Predictive analytics powered by AI can provide insights into potential future property values and market trends. This feature equips buyers with crucial information, reducing the risks associated with property investments.

🕵️‍♂️ My personal usage of AI to find investment rental properties

A few years ago, I started my journey of investing in real estate rentals. To make a good investment, it's important to consider a multitude of different factors, such as location, market rent, property value, interest rate, and many more. Finding great rental investment opportunities is very time-consuming, requiring not only extensive connections but also the analysis of numerous deals available on the MLS (Multiple Listing Service). It's necessary to calculate metrics such as Net Operating Income, Cap Rate, Cash Flow, Cash on Cash Return, among others. Often, these calculations are done manually, property by property, using custom spreadsheets or calculators.

To streamline this process, I created my own AI project, which I named ActiveListings. This system automatically calculates all these metrics for all the listings in your market of choice, taking into account the current market conditions and interest rates. As a result, you can filter, sort, and compare properties to strategically find great investment opportunities.

In this side project, which I built in just a few hours, I was able to outperform the housing market, find under-market value listings, and automatically analyze hundreds of data points. This provided me with the essential metrics needed for investing in profitable deals.

My system was designed to provide me with a daily batch update of all MLS listings in a specific market, complete with all the calculated metrics. From there, it's easy to filter and sort by specific metrics and receive recommendations on offers to ensure a great return on investment.

Try Active Listings

A prototype to find great investment Real Estate opportunities

Try ActiveListings
User Interface of Active Listings prototype to find good real estate listings

🛠️ My Tech Stack to Build Active Listings

Utilizing state-of-the-art No-Code AI tools, I meticulously engineered this prototype. The technology stack used is as follows:

  • Apify: used to scrape Listings from Zillow, Realtor, and others with pre-built templates available in their marketplace.
  • Rentometer: this solution provides an easy way to get rent estimates compared with other local properties.
  • Zestimate & Corelogic: get up to date estimate value for a given property address, taking into account inputs such as location, number of bedrooms, square footage, etc.
  • Parabola: it is the glue that brings all the pieces together and automates the entire workflow.
  • Airtable: used to build the end user interface to easily digest the results.
  • Akkio: used to train the ML models to make the purchase price recommendation.
No-code AI architecture to find great Real Estate Opportunities

Future improvements:

  • Computer Vision: All listings come with pictures of the properties and AI can be used to analyze the pictures and detect the conditions, for example, if it needs remodeling or the style. Those values can be used for a wedge finder or as input to estimate the value of the property.
  • Chat Interface: the next logical step is to add a Natural Language interface to navigate the data. Zillow has launched a new AI-powered natural language search feature that lets shoppers search for homes in the same way they would talk to their friends and family. For example, you can type in "3 bedroom homes in San Francisco with a view" or "open houses near me this weekend" and Zillow will return relevant results. This new feature is a first in the real estate industry and is a major step forward in making the home buying process easier and more convenient for consumers. It is also available as a chatGPT plugin.
Zillow ChatGPT Plugin to search for Real Estate

⚠️ Understanding the Risks

While AI brings many benefits to the real estate property search process, there are potential risks to consider. Over-reliance on AI is a risk as it could replace critical human judgment, especially in complex property transactions. A good example is Zillow's venture into direct home buying in 2019, which relied on an algorithm to set purchasing prices, resulting in significant losses for the company. The algorithm failed to fully account for the complexities of the housing market, such as location, condition, and market conditions, leading to poor buying decisions. Moreover, Zillow's rapid buy-and-sell strategy left no time for home improvements, making properties less appealing to potential buyers. The company's losses forced it to abandon this approach and offload the properties it had bought. Zillow's experience serves as a warning for other companies considering algorithm-based decision-making, underlining that such systems cannot entirely replace human judgment.

Bias in training data can also skew AI results, leading to inaccurate property recommendations. AI's inability to account for unforeseen market changes emphasizes the importance of combining AI insights with expert human judgment.

🔮 The Future of Real Estate Property Search is AI

The role of AI in real estate is only set to increase. With ongoing advancements in AI technology, we can expect even more sophisticated property search capabilities in the future. For example, virtual reality (VR) integrated with AI could allow potential buyers to take virtual tours of recommended properties based on their preferences, further enhancing the property search process.

AI is not just a passing trend but a significant shift in the way we search for properties. As the technology continues to evolve, it will undoubtedly redefine the real estate landscape, making the property search process more efficient, accurate, and customer-centric. So, whether you're a buyer looking for your dream home or a real estate professional striving to provide top-notch service to your clients, embracing AI could be the key to a smoother and more successful property search experience.

Written by
Armand Ruiz
I'm a Director of Data Science at IBM and the founder of I love to play tennis, cook, and hike!
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