When identifying conservation priorities, the accuracy of conservation assessments is constrained by the quality of data available. Despite previous efforts exploring how to deal with imperfect datasets, little is known about how data uncertainty translates into errors in conservation planning outcomes. Here, we evaluate the magnitude of commission and omission error, effectiveness and efficiency of conservation planning outcomes derived from three datasets with increasing data quality. We demonstrate that investing in data acquisition might not always be the best strategy as the magnitude of errors introduced by new sites/species can exceed the benefits gained. There was a trade-off between effectiveness and efficiency due to poorly sampled rare species. Given that data acquisition is limited by the high cost and time required, we recommend focusing on improving the quality of data for those species with the highest level of uncertainty (rare species) when acquiring new data.