Predictive Analytics Helping to Boost Real Estate Business
SAN FRANCISCO (November 9, 2013) – Predictive analytics, or evaluating and interpreting data to predict future outcomes and trends, is helping the real estate industry better understand transaction and market data and use it to benefit the industry, agents and consumers.
Realtors® and attendees at today’s “Emerging Business Technology” forum during the 2013 REALTORS® Conference and Expo gained insights into predictive analytics and leveraging data to help Realtors® and local and state associations make better business decisions.
The National Association of Realtors® recently launched a new Predictive Analytics group that will examine and analyze member and customer trends from a variety of data sets to help the association determine and develop services and resources that provide value to Realtors® and give them insights into ways they can better meet the needs of their clients.
During the session, NAR Managing Director of Data Analytics Todd Carpenter said the goal is to use disparate data sources to build analytical models that will solve complex problems in the housing industry and to develop tools to help Realtors®, state and local associations, and others make better data driven decisions.
“By listening more to members and customers, organizations will be better able to meet their needs,” he said. “NAR has a mountain of its own data, such as its monthly existing-home sales data, and relationships with other data sources. Analyzing this data will help us learn more about our members and their businesses and clients.”
Carpenter said NAR’s new Predictive Analytics group is moving forward in three phases. They are currently in the experimentation phase, analyzing the data to find trends and patterns. He said the next two phases are to develop partnerships with other data providers, and then to begin designing and building products for members.
Realtor® Ted Loring, chair of NAR’s Data Strategies committee, said real estate is all about relationships; the goal of predictive analytics is to figure out how to add value to the relationship to make it stronger.
“By applying predictive models to data, an organization can uncover behavioral patterns and develop models to guide targeted interactions, and ultimately achieve overall operational effectiveness and higher marketing return on investment,” he said.
Loring said traditional analytics collect propriety big picture data and analyze it to give retrospective insight into what happened; customer relationship management tools look at the little picture and analyzes proprietary data that support current activities. Big data looks at both the little and big picture and analyzes public and proprietary data to determine patterns that can predict the future.
“Linking information can give you an incredibly detailed picture,” he said. “NAR’s strategy going forward is to determine the strategy and initial objective, identify models worth emulating, assess existing Realtor® resources, acquire and develop missing capabilities, run a pilot project, and then scale up.”
The National Association of Realtors®, “The Voice for Real Estate,” is America’s largest trade association, representing 1 million members involved in all aspects of the residential and commercial real estate industries.
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