The National Association of REALTORS® Brokers Value for Members with DataRobot
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- DataRobot’s enterprise AI platform
Tech Stack
- Data Science
- Machine Learning
- Predictive Modeling
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Predictive Analytics
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Predictive Maintenance
Services
- Data Science Services
About The Customer
The National Association of REALTORS® is America’s largest trade association, representing over 1.4 million members around the country. Their members include brokers, salespeople, property managers, counselors, and others engaged in all aspects of the real estate industry. Its goal is to ensure that its members are at the forefront of the real estate industry, impacting public policy, educating clients on emerging technologies, real estate markets and best practices, and improving the communities in which they live. With so many members from unique backgrounds with varying professional interests, each looking for something different out of their membership, delivering value to them requires NAR to truly know their members well.
The Challenge
The National Association of REALTORS® (NAR) is America’s largest trade association, representing over 1.4 million members around the country. Their members include brokers, salespeople, property managers, counselors, and others engaged in all aspects of the real estate industry. With so many members from unique backgrounds with varying professional interests, each looking for something different out of their membership, delivering value to them requires NAR to truly know their members well. To do that, NAR turned to the data. However, the association was trying to become more data-driven, and so was focused on higher-level objectives like understanding its members better and solving business problems that impacted its members. But because of the nature of how the two data scientists operated — without a centralized team or the appropriate resources - communication and feedback loops around data science projects were inefficient, and negatively impacted the ability of the data scientists to deliver value.
The Solution
NAR evaluated various data science and machine learning tools that could both increase their productivity while also enhancing AI adoption throughout NAR. They eventually entered into a Proof-of-Concept with DataRobot, with a test use case to predict which of their members were most likely to attend the association’s REALTORS® Conference & Expo, the largest annual event for the most engaged real estate professionals. The team’s goal was to identify a segment of members most likely to attend the conference, and with the support of the Marketing and Communications team encourage those members to attend and check out the educational and networking opportunities available at the conference. Using DataRobot’s enterprise AI platform to substantially boost data science productivity and efficiency, Aleksandar’s team builds and deploys predictive models to help NAR make more optimal decisions, and ultimately better serve its members.
Operational Impact
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