Big data Presentation from REALTOR Party Convention
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An explanation on how big data is being used at National Association of Realtors and in education in the real estate sphere.
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Big data Presentation from REALTOR Party Convention
- 1. How it is Transforming Learning
- 12. Data Analytics Group Update Todd Carpenter
- 13. A holistic member profile
- 14. A holistic member profile • Votes • Advocates • Donates • Campaigns
- 15. A holistic member profile • Attends events • Pays for education • Uses RPR • Opens Newsletters • Calls the 800 number • Logs into realtor.org • Downloads Member Center app • Contacts other departments • Volunteers for leadership • Comments on social media • Votes • Advocates • Donates • Campaigns
- 16. Information we collect • www.realtor.org/privacy-policy • Contact information • Tracking information • Volunteered information Realtor.org privacy policy
- 17. Information we license • Demographics data • Address verification • Voter record data
- 18. Information we plan to sell
- 20. NAR’s focus on data security http://www.realtor.org/topics/data -privacy-and-security
- 21. Applying predictive analytics to MMPS
- 22. Collecting data over time Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA
- 23. Collecting data over time Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA
- 24. Collecting data over time Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA
- 25. Collecting data over time Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA Early patterns
- 26. Collecting data over time Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA Steps to move member up the ladder
- 27. Collecting data over time Attends Local YPN Event Volunteers for a Committee Attends RPCTE Earns ABR Designation Donates to RPAC Responds to CFA Long term goals
- 28. What we want to predict • Future net-promoters • Future volunteer leaders • Future advocates • Communication segments • At-risk members • Rising stars • Future consumers of association products and services
- 29. Benefits to members • More appealing communications • More effective goods and services • More fellow advocates
- 30. QUESTIONS? Todd Carpenter Managing Director of Data Analytics tcar@realtors.org
Notas del editor
- The best way to solve this problem is to use monthly WAR (wins above replacedment) data, which the good folks of FanGraphs were able to provide. We looked at WAR and WAR distribution for the month of April each year from 1974 through
- We have been collecting information about our members for decades. The most common example is the information in NRDS. This information is shared between associations, but not with the general public.
- NAR’s divisions also collect their information about members. For instance, CPA collects data about RPAC donations and responses to calls for action.
- The biggest advantage to MMPS is that each department will have more information about the member’s association activities.
- We already have a privacy policy in place that is posted to realtor.org. The data analytics group is working with NAR’s general council to assure that the associations actions honor the privacy of it’s members.
- We have been licensing data about both consumers and our members for a few years now. Our voter data is compiled directly from state and county government sources. Demographic data comes from credit boroughs that collect it from sources like loan and credit card applications. We share aggregate reporting with organizations like our Strategic Benefits Partners. We may expand expand this licensing to use this data association wide. We’re also considering tools and services for data acquisition regarding state licensing, MLS data, and user generated content programs.
- This one’s blank because we don’t have plans for that.
- Our own data would be greatly enhanced by measuring similar member activities at the state and local association levels. In addition, there may be opportunities to work with strategic partners, including MLSes, Realtor.com, and others. In each case, the legal affairs team will be involved to assure any executed sharing agreement is consistent with our policies.
- Data security has been a focus of the legal affairs team for several years. In 2011, Katie Johnson released a Data Security and Privacy Toolkit for our members and we maintain a dedicated page of resources on realtor.org. As General Counsel, Katie remains personally involved in matters around data privacy as they pertain to our members.
- Not only do we want to assemble this data in one place, we want to measure the points of entry over time. This simplified example could measure a member’s interactions over the course of several years.
- Soon we will be able to match the timeline’s of one member to another.
- Then, when a common pattern begins to emerge, we can begin to apply the pattern to other members. In this case, if the association’s goal is to increase CFA responses, then this hypothetical pattern suggests what common steps many members take before they start to respond to CFA’s.
- If the goal is to increase CFA responses, then we would identify members in the early stages of this pattern.
- We may offer marketing or communications to encourage these members to take the next steps up the ladder.
- The end result is accomplished by following a disperate path that may not have been apparent to our staff.