How Numinar conducts modeling for a fraction of the cost
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In the fall of 2022, two months from Election Day, the Republican Attorneys General Association needed to understand the political winds in four key races across the country: Abraham Hamadeh in AZ, Sigal Chattah in NV, Eric Toney in WI, and Jim Schultz in MN. They were looking for real-time updates to see where these crucial races stood and how they were changing.
RAGA was looking for a central voter data platform that could manage all their polling data from across multiple pollsters and also augment existing data with weekly tracking surveys.
Numinar provided the perfect solution with an incredibly easy to use voter data platform and machine learning modeling for a fraction of the cost. Within days, all outside polling data was uploaded into Numinar and 1.3M additional text and IVR surveys were being fielded each month, generating tens of thousands of additional survey respondents.
Numinar used the combined data to produce a new model each week leading up to Election Day to see where their candidates stood against their opponent, providing accurate results—just a 3.3% median margin of error—and saving thousands of dollars.
Pete Bisbee, Executive Director