High-quality biodiversity inventories are key tools to develop effective conservation strategies, but financial resources devoted to systematic species inventories are usually limited. Different sampling strategies have been proposed to efficiently allocate such limited resources (i.e. accessibility-based, stratified random and grid samplings), but their effectiveness may depend on the aim of the survey. Our aim was to assess which approach can provide the best trade-off between sampling costs and accuracy in estimating both single species distribution and species set composition. We generated simulated species distribution data to compare costs and performances of the three sampling methods in assessing species distribution. When we aim at measuring species range (i.e. area of occupancy or extent of occurrence), or obtaining baseline ecological data for conservation assessments (i.e. niche breadth), grid sampling usually provided the best trade-off between performance and costs at both the single- and multi-species levels. Otherwise, the stratified random sampling outperformed the other methods when we are interested in assessing the relative rarity (i.e. species frequency) of the species across the study area. Low quality distribution data can lead to heavily biased conclusions on biodiversity trends or impacts of environmental changes; our findings highlight that selecting the right sampling strategy is essential to obtain reliable estimates of both single species distribution and species set composition.