Survey researchers sometimes face several options to formally define and draw random probability samples from their target population of individuals. Relatively little is known about the consequences for the quality of survey estimates when different sampling frames are used, for example frames that list addresses versus individuals While the initial choice for a sampling frame design may be based on diverse criteria, we argue that any decision has consequences for the quality of survey esti- mates. We hypothesize that knowing respondents’ names upfront decreases nonresponse and coverage error. This can be accomplished by either using person-based sampling frames or augmenting nonperson- based sampling frames with names. We systematically compare sam- pling frame designs in the context of face-to-face surveys in connection with the European Social Survey (ESS) with the help of three quasi- experimental datasets from a single country. Even the most conservative measures support our hypothesis that the presence of names in the sam- pling frames could improve response rates, noncontact rates, cooperation rates, and ineligibility rates by between 2.5 and 6 percentage points. Additionally, the accuracy of population estimates could increase. These results suggest that survey researchers collecting individual-level data would be best advised to use well-maintained sampling frame designs (augmented) with person-specific information.