3 AI startups using predictive analytics to transform real estate

Startups like Housecanary and Quantarium are analyzing external data to better predict customer behavior, generate leads and automate processes in real estate.

Key Takeaway

Few industries have access to such enormous amounts of consumer data as real estate. Everyday, potential homebuyers and renters leave behind a plethora of online breadcrumbs that signal their intended next moves. Outside Insight can help stakeholders understand what to do with this data and how it can be used to make better, more forward-looking decisions.

Predictive analytics companies in the real estate industry have received high praise over the past year. A thought leadership survey conducted by Imprev in August 2017 and released at real estate conference Inman Connect found that two-out-of-three top real estate executives are more likely to invest in Predictive Analytics (65%), Marketing Automation (65%) and Big Data (64%) by 2022.

More surprising, however, is that only 20% rated real estate portals, such as Zillow or realtor.com®, as one of their “most important real estate marketing channels and technologies” in 2022. Rather, they predict Mobile Apps (48%), Social Media (45%) and Video (44%) will be more important.

Why is predictive analytics so important to the real estate industry? According to Dave Garland, partner, Second Century Ventures and Director of Strategic Investments for the National Association of REALTORS® at RISMedia’s 2017 Real Estate CEO Exchange, “Predictive analytics is analyzing extracted data, using old data to predict the future. The big difference now is we have new data points that we can apply to our industry. We’re moving from the idea of hindsight to insight to foresight.”

The big difference now is we have new data points that we can apply to our industry. We’re moving from the idea of hindsight to insight to foresight.

Quantarium ‘crystal ball’ predicts portfolio’s next move

Data science startup Quantarium gathers data from more than 145M households in the US to help real estate agents better visualize information associated with a property and to predict when homeowners in their portfolio are likely to make a move.

Erick Watson, VP of Corporate Development at Quantarium said via Timextender: “We aggregate and curate residential real estate data to help buyers and sellers accurately price their homes.” Their model is called an Automated Valuation Model, or AVM. This type of algorithm is commonly used in the mortgage industry to value a property.

“Historically, Residential Brokers were the intermediaries that helped you identify these criteria and make your purchase decision,” Watson said. “Now, empirical data is available that can help you make an even better, more informed decision.”

He identified 2 key challenges when it comes to data in the real estate industry:

1. Predicting the behavior of people who have interacted with a property

2. Curating and normalizing the massive quantities of data available

The most significant challenge, however, is to gather data related to a prospect’s personal life while still respecting the individual’s privacy. “Our job is to predictively figure out which homes are going to be bought or sold, and at what price, so that we may contribute to a more efficient marketplace and ease the burden of real estate transactions.”

According to Watson, there’s a lot of information that can be gleaned from the online breadcrumbs we leave behind when completing everyday transactions. Rather than relying on internal data from within an agency or brokerage firm, or basing decisions on past behaviors, Quantarium’s technology allows agents to use those external clues to predict future behavior and remove a lot of the manual elements surrounding the data collection process.

HouseCanary arms agents and homeowners with data-driven decision-making tools

At the core of San Francisco-based real estate tech startup HouseCanary is its predictive analytics, enabling stakeholders across the real estate industry to make better, more informed decisions. The platform offers precise property details, valuations, forecasts and LTV at a 3-year forecast, based on a number of external data inputs.

According to RIS Media, HouseCanary can accurately value and forecast over 18,000 U.S. zip codes, 3 million blocks and 100 million properties. Its home price indices are now part of Google’s Cloud Platform data offering for financial institutions.

CEO Jeremy Sicklick claims the product’s real value lies in its ability to scrub, organize and analyze large, disparate data sets and create a single point of credible insight. “Other home valuation methods are based largely on historical comparable sales,” he said. “HouseCanary measures price movements on every residential block in the country, allowing for precise valuations today and three years into the future.”

This predictive insight offers real estate professionals and prospective customers a clear competitive advantage – arming them with the ability to determine why a particular valuation was calculated – and continually learns based on inputs from real estate agents on the platform. The tool analyzes external data points including market demand, months-of-supply, macroeconomic data, rental values, capital markets, jobs, traffic. It even looks at views from a property’s backyard.

External data points evaluated by HouseCanary

Market demand

Macroeconomic data

Rental values

Capital markets



Rex Real Estate Exchange bot cuts fees, targets prospects using online data

Developed by former Goldman Sachs executive Jack Ryan, Rex Real Estate Exchangeis an AI bot – an alternative to traditional brokers – that makes the process of buying and selling residential real estate easier, cheaper and more efficient for both parties.

According to the New York Post, the bot can answer nearly any question from a prospective buyer — from when the roof was last repaired to where the nearest Starbucks is. More importantly, it deploys advanced analytics, combining its own data with that of IBM Watson, Amazon Alexa and Google AI, to precisely target prospective buyers and serve them ads.

“Rex gathers big data online on potential customers beyond their search histories to ‘target those people with ads so effectively they will click on them because we know who they are,’ says Ari Sternberg, Rex’s head of digital marketing.

Today, 89% of sellers use a broker, while only 8% of homes are For Sale By Owner. Rex is trying to increase that 8 percent number by being super smart. By using Rex, Ryan says, homeowners save $25,000 on average, paying Rex only 2% vs the traditional 6% for brokerage fees.

With the application of any big data technology comes concern over job loss due to automation. But experts in the industry remain confident the human element is still essential. The difference now is much of the guesswork and the veil of secrecy around valuations has been removed.

According to Scott MacDonald, broker/owner and president of RE/MAX Gateway, it’s all about giving agents the best tools to use. “You have the discounters, the disruptors and the DIYers,” he said. “The more you can arm your agents with information about what happened in the past and what’s coming in the future, the better able they will be to serve their clients.”

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