Boiling dynamics and related heat transfer mechanisms have been widely studied for several decades. During that time, incredible progress has been made on quantifying bubble departure phenomena including growth rate, departure frequency, associated natural and forced convection, and radiation additions to the overall heat transfer rate. With this, the thermal community has been able to fully characterize the boiling curve throughout its distinct regimes; natural convection, isolated bubble, fully developed nucleate boiling, transition, and film boiling. Previous work has primarily been focused on what heat transfer coefficients are achievable, how to reduce incipience overshoot, and increasing the Critical Heat Flux (CHF). These findings have proven critical in developing analytical solutions to predict boiling characteristics without performing time intensive and high cost experiments. Even with these models, they tend to only be accurate for specific fluid/surface combinations, and they have been extensively studied. As new surfaces emerge and claims of incredible thermal performance arise, there has been no consistent way to substantiate those claims. The community does not have a standard test for boiling heat transfer effectiveness. The best way to determine the effectiveness of a two-phase heat transfer surface is to extract as much heat from it while using as little quenching coolant as possible. This study quantifies that value, the net coolant flow rate to a boiling surface, for a plain, microfinned, and microstructured copper surface. Particle Image Velocimetry (PIV) is used to quantify the requisite quenching fluid flow rate needed to sustain nucleate boiling without onset of the catastrophic CHF event. By comparing the net coolant flow rate of one standard/bare/plain surface to an enhanced one, a boiling surface effectiveness parameter is developed. This would be similar to that of a fin effectiveness parameter as this quantifies the utility of adding fins to an otherwise bare surface. The experimental data presented in this work was also compared to an analytical model showing that this coolant flow rate to the surface can be predicted to within 4% and 30% error at low and high heat fluxes, respectively.