The strength of the analyte-substrate interaction is a key component when evaluating the observed enhancements in surface-enhanced Raman scattering (SERS) detection. By performing Raman and electrochemical measurements on a series of neurotransmitters, including dopamine, serotonin, norepinephrine, and epinephrine, as well as catechol as it allows us to examine the diol moiety without the side chains present, we were able to correlate surface chemistry with the measured SERS signal and examine the oxidation mechanism of each analyte. Finite element simulations of fluid flow, mass transport, and Langmuir adsorption to a surface in a microchannel were used to expand on the experiments. By holding kads constant and changing kdes, Keq was varied systematically to elucidate how the adsorption kinetics change for different molecular adsorbates. The modeling indicates that the largest surface concentration is observed from the analyte with the strongest affinity for the surface in both the continuous flow and time dependent injection scenarios. The COMSOL model of varying surface concentration explains differences observed in integrated current during amperometry and signal intensities in SERS measurements. This combination of results indicates that molecular structure and surface affinity influence the sensitivity in SERS, such that the species with the strongest affinity for the surface has the highest signal-to-noise in the SERS experiments in flowing solutions.