Declining telephone response rates have forced several transformations in survey methodology, including cell phone supplements, nonprobability sampling, and increased reliance on model-based inferences. At the same time, advances in statistical methods and vast amounts of new data sources suggest that new methods can combat some of these problems. We focus on one type of data source—voter registration databases—and show how they can improve inferences from political surveys. These databases allow survey methodologists to leverage political variables, such as party registration and past voting behavior, at a large scale and free of overreporting bias or endogeneity between survey responses. We develop a general process to take advantage of this data, which is illustrated through an example where we use multilevel regression and poststratification to produce vote choice estimates for the 2012 presidential election, projecting those estimates to 195 million registered voters in a postelection context. Our inferences are stable and reasonable down to demographic subgroups within small geographies and even down to the county or congressional district level. They can be used to supplement exit polls, which have become increasingly problematic and are not available in all geographies. We discuss problems, limitations, and open areas of research.