GoDig, a platform for targeted pathway proteomics without the need for manual assay scheduling or synthetic standards, is a powerful, flexible, and easy-to-use method that uses tandem mass tags to increase sample throughput up to 18-fold relative to label-free methods. Though the protein-level success rates of GoDig are high, the peptide-level success rates are more limited, hampering assays of harder-to-quantify proteins and site-specific phenomena. To guide the optimization of GoDig assays as well as improvements to the GoDig platform, we created GoDigViewer, a new stand-alone software that provides detailed visualizations of GoDig runs. GoDigViewer guided the implementation of "priming runs," an acquisition mode with significantly higher success rates. In this mode, two or more chromatographic priming runs are automatically performed to improve the accuracy and precision of target elution orders, followed by analytical runs which quantify targets. Using priming runs, success rates exceeded 97% for a list of 400 peptide targets and 95% for a list of 200 targets that are usually not quantified using untargeted mass spectrometry. We used priming runs to establish a quantitative assay of 125 macroautophagy proteins that had a >95% success rate and revealed differences in macroautophagy expression profiles across four human cell lines.