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Discovery Platform

ABOUT THE AUTHOR
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Today’s Data Is Tomorrow’s Bigger Picture

How can companies drive data rather than letting data drive them?

Data tells stories. In the property industry, there are few tactics more powerful than a compelling story; however, the transition from aspirational narratives into real, on-the-ground projects is accelerating.

As is the case in so many industries, the push for bigger wins, more efficiency and increased personalization has resulted in more companies favoring data-driven decisions. Within the property technology space, successfully achieving desired outcomes can require sifting through hundreds, thousands or even millions of data points.

The problem is that more than three-quarters of businesses surveyed in a recent survey commissioned by CoreLogic reported that data sources are fragmented, difficult to rationalize and a struggle to integrate.

Follow the Yellow-Brick Road

Big data solutions that can process millions of bytes of data to provide intuitive and strategic insights can be a large investment — one which not all property businesses are ready to make.

“Significantly less than half (42%) of PropTech professionals surveyed reported returns on investment from big data and artificial intelligence initiatives that exceeded $1 million, as leaders struggle with fragmented data sources, integration challenges and talent to identify and exploit the insights that will set them apart from the pack in this extraordinarily competitive environment,” says John Rogers, Chief Innovation Officer of CoreLogic, whose team commissioned the study.

However, this hesitancy to invest heavily in big data is changing. Sixty-five percent of survey respondents said their companies are placing additional financial resources into property-related big data and artificial intelligence (AI) in 2022 as compared to 2021.

“Digital transformation programs that leverage cloud infrastructure, data science and analytics support companies working to foundationally understand, improve and grow their businesses,” says CoreLogic Business Development Principal Mark Weaver. “Big data and AI are what permit organizations to accelerate their timeline in bringing solutions to market as well as extract meaningful returns on investment from these initiatives.”

Investment in data within the property industry space is spreading. Venture capitalists have also taken note of the value that these terabytes of data hold. In 2021, venture capital investment into real estate tech reached a record-breaking $32 billion, a 28% increase in funding since 2020, according to The Center for Real Estate Technology & Innovation (CRETI).

Clearly, PropTech investment is no longer a niche area. In fact, for companies seeking to provide cleaner data, connect industry professionals with willing buyers or even integrate ESG initiatives, data-powered solutions are becoming the gold standard rather than the exception.

While the need for high-quality data is not new, PropTech uses swaths of information that can be collected in innovative ways. Large companies often favor turnkey solutions to best connect with their customers, but both start-ups and legacy corporations now more frequently seeking raw data to perform in-house analysis and determine how market information affects their foundational operations.

The Goldilocks Solution

Although data and analytics are gaining market share against prepackaged solutions in the property industry, Weaver theorizes that raw data will not necessarily overtake these established offerings. Instead, the need to independently manipulate large datasets to best understand customer needs will drive innovation within existing mortgage, insurance and real estate industry solutions.

“Having the capability to access large datasets while simultaneously relying on tailored SaaS products is the Goldilocks solution that enables companies to create more efficient operations models based on cutting edge infrastructure, data science and analytical capabilities,” says Weaver who emphasizes that as digital innovation forces companies to innovate quicker, not all enterprises are yet equipped to roll out big-data analytics at the proper scale.

Synthesizing data that responds to an ever-changing market while also offering a historical perspective is a task that requires scrupulous data management and a vast archive of information that has evolved over decades. Rather than build such an archive, many property companies are opting to simplify data science by relying on partners to seamlessly integrate data into solutions that accelerate innovation, mitigate risk and identify new revenue streams. In fact, 40% of those that responded to CoreLogic’s survey said they work with third-party providers to harvest meaningful business insights and outcomes from data.

Discover a New Way to Manage and Analyze Property Big Data

To help the real estate industry better manage and analyze critical data, CoreLogic has launched the Discovery Platform.™ This secure, cloud-based data exchange and analytics platform is built on more than 50 years of data spanning 99.9% of U.S. properties. Discovery’s key features include:

  • Access to CoreLogic’s vast library of market-leading industry data, including information on property values and characteristics, geospatial boundaries, environmental/natural disaster considerations and individual neighborhoods.
  • Integration with customers’ existing data, making it easier and faster to manage, analyze and understand information to inform key business decisions.
  • Modeling and visualization tools to help extract insights from large sets of data.

Discovery allows enterprises to solve problems and predict outcomes across every aspect of a business, from analyzing risks and competitors to prospecting sales leads to profiling customer needs. To learn more about an ecosystem that can simplify data challenges while providing expert guidance on how to best meet the data demands of today’s market, visit CoreLogic’s Discovery Platform. Today’s data is tomorrow’s bigger picture.

© 2022 CoreLogic,Inc., All rights reserved.
ABOUT THE AUTHOR
Data Team
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