Solid phase microextraction (SPME) is a versatile, non-exhaustive sample preparation tool that has been demonstrated to be well-suited for facile and effective analysis of a broad range of compounds in a plethora of studies. A growing number of reports describing diverse SPME workflows for novel investigations in a variety of fields, such as flavor and fragrance investigations, environmental studies, and diverse bioanalytical applications, among others, corroborate the applicability of this microextraction tool in the analytical sciences

Matrix effects can significantly impede the accuracy, sensitivity, and reliability of separation techniques presenting a formidable challenge to the analytical process. It is crucial to address matrix effects to achieve accurate and precise measurements in complex matrices. The multifaceted nature of matrix effects which can be influenced by factors such as target analyte, sample preparation protocol, composition, and choice of instrument necessitates a pragmatic approach when analyzing complex matrices. This review aims to highlight common challenges associated with matrix effects throughout the entire analytical process with emphasis on gas chromatography‐mass spectrometry, liquid chromatography‐mass spectrometry, and sample preparation techniques. These techniques are susceptible to matrix effects that could lead to ion suppression/enhancement or impact the analyte signal at various stages of the analytical workflow. The assessment, quantification, and mitigation of matrix effects are necessary in developing any analytical method. Strategies can be implemented to reduce or eliminate the matrix effect by changing the type of ionization, improving extraction and clean‐up methods, optimization of chromatography conditions, and corrective calibration methods. While development of an effective strategy to completely mitigate matrix effects remains elusive, an integrated approach that combines sample preparation, analytical extraction, and effective instrumental analysis remains the most promising avenue for identifying and resolving matrix effects.