An iterative feedback optimization methodology has been introduced as a complementary approach to conventional real-time optimization (RTO) methods to improve plant operation without requiring repetitive model updating. In this paper, the results analysis component that is an integral part of an RTO system is developed for use with iterative feedback optimization to evaluate the inherent variability of the optimization results transmitted from the plant measurements. Only optimization results that represent meaningful changes are implemented as the new setpoints, thus reducing unnecessary and profitless corrective actions. The effectiveness of the proposed results analysis method is tested on a simulated CSTR process.