We introduce a novel monthly county-level consumption dataset constructed from spending data on over 350 million credit cards in the Federal Reserve’s Y-14M reports, covering more than 3,000 U.S. counties since 2014. We first show that the data closely approximate traditional consumption measures, explaining 92 percent of the variation in monthly adjusted personal consumption expenditures (PCE) growth at the national level and 88 percent at the annual state level. We then exploit the high frequency and geographic granularity of the data to estimate heterogeneous consumption responses to monetary policy shocks across the county-level income distribution, an analysis infeasible with traditional data sources. We find that low-income counties exhibit substantially larger spending declines than high-income counties, consistent with predictions of heterogeneous agent New Keynesian models.