This study explores normative feedback as a way to reduce rating errors and increase the reliability and validity of structured interview ratings. Based in control theory and social comparison theory, we propose a model of normative feedback interventions (NFIs) in the context of structured interviews and test our model using data from over 20,000 interviews conducted by more than 100 interviewers over a period of more than 4 years. Results indicate that lenient and severe interviewers reduced discrepancies between their ratings and the overall normative mean rating after receipt of normative feedback, though changes were greater for lenient interviewers. When various waves of feedback were presented in later NFIs, the combined normative mean rating over multiple time periods was more predictive of subsequent rating changes than the normative mean rating from the most recent time period. Mean within-interviewer rating variance, along with interrater agreement and interrater reliability, increased after the initial NFI, but results from later NFIs were more complex and revealed that feedback interventions may lose effectiveness over time. A second study using simulated data indicated that leniency and severity errors did not impact rating validity, but did affect which applicants were hired. We conclude that giving normative feedback to interviewers will aid in minimizing interviewer rating differences and enhance the reliability of structured interview ratings. We suggest that interviewer feedback might be considered as a potential new component of interview structure, though future research is needed before a definitive conclusion can be drawn.