Realistic response rate expectations are important for successfully allocating and managing data collection efforts under limited resources. Interviewer performance is often evaluated against response rate standards, and face-to-face interviewer performance can vary due to, in part, the socioeconomic characteristics of the neighborhoods in which they work, reflecting well-documented differences in survey participation by these characteristics. In this article, we describe a method to establish unified, data-driven response rate standards to evaluate field interviewers. Using U.S. Census and American Community Survey data at the block-group level of geography, we identify correlates of 2010 census participation and cluster the block groups into homogeneous strata. The resulting clusters vary in meaningful ways to differentiate participation rates in household surveys. We use response rates by cluster to establish interviewer response rate standards for these sample surveys. We describe the process for simulating response rate distributions and the procedure for identifying performance-level cutoffs.