A thorough characterization is fundamental not only during therapeutic development of any biotherapeutic product, but also during quality control. An assay of this type requires comprehensive characterization as well as quantitative tracking of product quality attributes (PQAs). Previous approaches mainly used peptide mapping with collision induced dissociation (CID) MS/MS for characterization and a subsequent MAM that leveraged the MS level. Here, a novel fragmentation type based on electron activated dissociation (EAD) was investigated to combine information-rich fragmentation with an accurate MAM assessment in a single injection. The trastuzumab digest was run in 5 technical replicates with EAD MS/MS to determine the applicability of this new form of fragmentation for reproducible identification and monitoring compared to the well-established CID-based analysis. Both data sets showed very similar, highly reproducible sequence coverages of up to 97%. Notably, an improved fragment coverage was achieved with EAD. This was linked to enhanced descriptive fragmentation of glycosylated and large, unmodified peptides. EAD allowed for up to 100% fragment coverage, including identification and localization of modifications that often pose a challenge to CID, such as glycosylations. In addition, the subsequent conversion of Asp to isoAsp from deamidated species could be detected due to the formation of indicative fragments. The same MS data were then used to perform relative quantification on a group of selected PQAs. A processing workflow was defined based on MS1 extracted peaks of the modified and unmodified forms of multiple charge states of the peptides of interest. Modifications were chosen to cover a broad range of relative abundances to understand the method’s capabilities for identification and MAM. Low abundant modifications included methionine oxidation (0.6–0.9%) and deamidation (0.5–1%), and high abundant modifications such as glycosylations and C-terminal lysine loss were selected for MAM. Reproducibility was assessed based on replicate analysis.