While many scholars have moved toward using individual-level data to test theories of distributive politics, no studies have ever explicitly examined differences between individual and aggregate analyses of a distributive program. By leveraging nationwide individual-level data on both revealed voter preferences and the actual receipt of particularistic benefits through a contemporary Venezuelan land reform initiative, this article demonstrates that scholars can most effectively test and refine individual-level theories of distributive politics by combining both individual- and macro-level data. There are at least two advantages to doing so. First, comparing and contrasting findings from data at different levels of analysis can enable researchers to paint a more complete picture of distributive targeting. Second, when distributive benefits can be impacted or redirected by subnational politicians, as is common with many distributive programs, individual-level data alone can generate mistaken inferences that are an artifact of competing targeting attempts at different levels of government instead of initial targeting strategies. I demonstrate both of these points and discuss practical and simple recommendations regarding data collection strategies for the purposes of effectively testing theories of distributive politics.