Driving Major Returns from Big Data and Data Science Investments in the Prop Tech Sector
Findings from CoreLogic Survey: The Role of Data Science in Deriving Greater Insights into Property Market Dynamics
Few industry segments depend more on getting the most out of investments in big data analytics and data science than the property technology (PropTech) sector. However, when it comes to finding insights from hundreds of thousands -- if not millions (sometimes billions) -- of data points to drive desired business outcomes, PropTech leaders may be falling short of meeting expected performance objectives, according to a recent BTR-100 survey commissioned by CoreLogic.
“Significantly less than half (42%) of PropTech professionals surveyed reported returns on investment from big data and AI initiatives that exceeded $1 million. Leaders struggle with fragmented data sources, integration challenges and talent to identify and exploit the insights that will set them apart from competitors in this extraordinarily competitive environment,” says John Rogers, Chief Innovation Officer of CoreLogic, whose team commissioned the study, entitled: The Role of Data Science in Deriving Greater Insights into Property Market Dynamics.
Specific reasons for suboptimal performance of data science operations cited by senior data science, business intelligence and technology management professionals in the survey, include:
Fragmented data sources are difficult to rationalize -- 45%
Internal and external data is difficult to integrate -- 40%
Transition from analysis to intelligent modeling is too slow -- 36%
Absence of dedicated solutions optimized for property data-analytics -- 35%
Lack of internal maturity with AI/ML applications -- 31%
Data scientists lack property-sector domain expertise -- 20%
“The volatility in today’s housing market places a premium on having the most up-to-date information for those operating in markets related to property,” says Rogers. “It is difficult for property-related companies to handle all the variables that influence price forecasting. It is for this reason that big data analytics and modeling are quickly becoming critical components for property-related companies.”
According to the survey, 56% or respondents characterized big data analytics and data science initiatives in their organizations as being in a mature state (though only 9% described their programs as being “very mature”).
“This shows the priority that is being placed by this sector on data science and big data analytics. Property-related companies are leveraging new tools and technologies to search for competitive advantages. It is the measurable ability to translate these investments into clear profitable outcomes and returns on investment that signal true success. This hinges on the effective integration of cloud technologies, data scientists and analytical data models with business strategy and execution,” explains Rogers.
Other findings from the CoreLogic BTR-100 Survey on The Role of Data Science in Deriving Greater Insights into Property Market Dynamics include:
76% of PropTech professionals say their organizations use external data sources to optimize analysis of property data.
69% of PropTech professionals say they are getting the full value expected from investments in data scientists to understand how market information affects business outcomes.
69% of ProTech professionals say their organizations invested more in AI and big data initiatives in 2021 than in 2020.
65% of PropTech professionals say their organizations will invest more in AI and big data in 2022 than they did in 2021
58% of PropTech professionals have generated $1 million or less in revenues from their AI and big data initiatives.
47% of PropTech professionals say their organization leverages a hybrid cloud/compute strategy to support AI and big data initiatives.
To learn about CoreLogic’s perspective on the AI and big data analytics trends that are shaping the PropTech sector, visit: http://www.corelogic.com/discovery-platform