Over the past decade, researchers have learned a great deal about the design and implementation of Web surveys. However, to date, we have virtually no empirical information about the role space and place has in influencing the error associated with Web-only surveys. The two types of error most often discussed when considering Web surveys are coverage and non-response; both of which are typically indicated as reasons for low response rates in these types of surveys. One way to pursue this issue of place is to use Geographic Information Systems (GIS) to spatially-model survey response rates. This will allow us to understand the impact of location on error in Web surveys. In this paper, we attempt to examine this gap in the literature by assessing the spatial clustering of response rates to a general population Web-only survey. The data come from a random, Address- Based Sampling approach using the Delivery Sequence File (Valassis version) where respondents received a postal letter with a URL. We calculate response rates at several geographic scales, including county, state, and region, to determine the extent to which response rates are spatially clustered. While controlling for ACS demographics, Internet availability, and postal characteristics, we then build a spatial lag model to measure spatial dependence of response rates observed. Preliminary findings show clusters of low response rates in the South that cannot be accounted for by other variables in the model.