Selective detection of coexisting species with similar reduction potentials using electrochemical approaches is very challenging. We employ material diversity at working electrodes to discriminate coexisting redox species such as dopamine, ascorbic acid and serotonin using a data-driven chemometric approach that exploits the subtle yet robust differences in characteristic CV curves for different working electrodes. We present these results using a simple and low-cost paper-based platform, containing different electrodes made of gold, carbon nanotube with and without nafion, reduced graphene oxide, and polyaniline with microfluidic delivery.